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2404.06473v2 | Generalized cubic partitions | A cubic partition consists of partition pairs $(\lambda,\mu)$ such that $\vert\lambda\vert+\vert\mu\vert=n$ where $\mu$ involves only even integers but no restriction is placed on $\lambda$. This paper initiates the notion of generalized cubic partitions and will prove a number of new congruences akin to the classical Ramanujan-type. The tools emphasize three methods of proofs. The paper concludes with a conjecture on the rarity of the aforementioned Ramanujan-type congruences. | Number Theory (math.NT) | The preprint contains a wrong conjecture and the paper's content will be completely changed from the current form. Not to be replaced | factual/methodological/other critical errors in manuscript | 14,069 |
2404.06850v3 | From naive trees to Random Forests: A general approach for proving consistency of tree-based methods | Tree-based methods such as Random Forests are learning algorithms that have become an integral part of the statistical toolbox. The last decade has shed some light on theoretical properties such as their consistency for regression tasks. However, the usual proofs assume normal error terms as well as an additive regression function and are rather technical. We overcome these issues by introducing a simple and catchy technique for proving consistency under quite general assumptions. To this end, we introduce a new class of naive trees, which do the subspacing completely at random and independent of the data. We then give a direct proof of their consistency. Using them to bound the error of more complex tree-based approaches such as univariate and multivariate CARTs, Extra Randomized Trees, or Random Forests, we deduce the consistency of all of them. Since naive trees appear to be too simple for actual application, we further analyze their finite sample properties in a simulation and small benchmark study. We find a slow convergence speed and a rather poor predictive performance. Based on these results, we finally discuss to what extent consistency proofs help to justify the application of complex learning algorithms. | Statistics Theory (math.ST) | [REDACTED-NAME] | factual/methodological/other critical errors in manuscript | 14,070 |
2404.06939v2 | Fast System Technology Co-Optimization Framework for Emerging Technology Based on Graph Neural Networks | This paper proposes a fast system technology co-optimization (STCO) framework that optimizes power, performance, and area (PPA) for next-generation IC design, addressing the challenges and opportunities presented by novel materials and device architectures. We focus on accelerating the technology level of STCO using AI techniques, by employing graph neural network (GNN)-based approaches for both TCAD simulation and cell library characterization, which are interconnected through a unified compact model, collectively achieving over a 100X speedup over traditional methods. These advancements enable comprehensive STCO iterations with runtime speedups ranging from 1.9X to 14.1X and supports both emerging and traditional technologies. | Emerging Technologies (cs.ET) | We found some errors in Figure.3 ,and we need some time to reconduct experiments. Therefore, we want to withdrawal our article now | factual/methodological/other critical errors in manuscript | 14,071 |
2404.07509v2 | Multiparameter cascaded quantum interferometer | We theoretically propose a multiparameter cascaded quantum interferometer in which a two-input and two-output setup is obtained by concatenating 50:50 beam splitters with n independent and adjustable time delays. A general method for deriving the coincidence probability of such an interferometer is given based on the linear transformation of the matrix of beam splitters. As examples, we analyze the interference characteristics of one-, two- and three-parameter cascaded quantum interferometers with different frequency correlations and input states. Some typical interferograms of such interferometers are provided to reveal more rich and complicated two-photon interference phenomena. In principle, arbitrary two-input and two-output experimental setups can be designed with the proposal. This work offers a toolbox for designing versatile quantum interferometers and provides a convenient method for deriving the coincidence probabilities involved. Potential applications can be found in the complete spectral characterization of two-photon states, multiparameter estimation, and quantum metrology. | Quantum Physics (quant-ph) | We have found a serious error in this version, which may mislead readers | factual/methodological/other critical errors in manuscript | 14,072 |
2404.08212v2 | Mental Stress Detection: Development and Evaluation of a Wearable In-Ear Plethysmography | Mental stress is a prevalent condition that can have negative impacts on one's health. Early detection and treatment are crucial for preventing related illnesses and maintaining overall wellness. This study presents a new method for identifying mental stress using a wearable biosensor worn in the ear. Data was gathered from 14 participants in a controlled environment using stress-inducing tasks such as memory and math tests. The raw photoplethysmography data was then processed by filtering, segmenting, and transforming it into scalograms using a continuous wavelet transform (CWT) which are based on two different mother wavelets, namely, a generalized Morse wavelet and the analytic Morlet (Gabor) wavelet. The scalograms were then passed through a convolutional neural network classifier, GoogLeNet, to classify the signals as stressed or non-stressed. The method achieved an outstanding result using the generalized Morse wavelet with an accuracy of 91.02% and an F1-score of 90.95%. This method demonstrates promise as a reliable tool for early detection and treatment of mental stress by providing real-time monitoring and allowing for preventive measures to be taken before it becomes a serious issue. | Signal Processing (eess.SP) | The paper is being withdrawn because we have identified substantial issues with the data analysis process. To ensure the integrity and accuracy of our findings, we are re-evaluating the data and will resubmit the paper after thorough revisions | factual/methodological/other critical errors in manuscript | 14,075 |
2404.08649v2 | Note: Applying the Brillouin Zone and Band Gap Leveraging AB Initio Calculation for Digital Well-Being: In-Depth Analysis of Band Structures in Information Spaces Insights from Solid-State Physics | The efforts of this Note are aimed at understanding various phenomena in digital space that are incomplete and difficult to define, and to translate them into language from research fields that are based on existing large-scale experimental data. Information diffusion and user behavior patterns in digital space are often hard to intuitively capture, and the principles and mechanisms behind them are difficult to articulate. To address this challenge, we have drawn on first-principles methods in physics, particularly solid state physics. This approach is known to be effective in analyzing the behavior of real physical materials at the atomic level and in understanding the electronic properties and bonding structures of materials. We have attempted to apply physical concepts based on first-principles calculations, in particular concepts such as first Brillouin zones, band gaps, and reciprocal lattice vectors, to digital space as a metaphor. This theoretical framework allows us to quantitatively and logically infer the behavior and trends of incomplete and ambiguous digital data and phenomena. For example, the "first Brillouin zone" of information in digital media indicates the potential sphere of influence of that information, and the band gap defines the threshold of influence for the information to be widely accepted. In addition, the reciprocal lattice vector serves as a boundary that indicates the limits of information characteristics and is an indicator of the degree to which a particular piece of information resonates with users. With this theoretical supplement, our research goes beyond the mere analysis of phenomena in the digital space and provides new methods for understanding and predicting the behavior of imperfect data and uncertain digital media. | Materials Science (cond-mat.mtrl-sci) | There are significant errors in the graphs of the simulations in the [REDACTED-NAME] paper, and there are a number of incorrect graphs, so I would like to withdraw and resubmit the paper. The author and others in the experimental physics field have pointed out that we need to verify the calculations again | factual/methodological/other critical errors in manuscript | 14,077 |
2404.09205v2 | Apparent violation of causality in relativistic quantum mechanics | In relativistic theories the principle of microscopic causality states that ``information cannot travel faster than the speed of light'' \cite{kaku}. In the present work we show that the time evolution of relativistic wave functions violates this principle. We consider here the wave functions of massless and massive particles. In the case of massless particles the wave functions which violate the microscopic causality have an analytic form while in the case of massive particles we have to rely on numerical calculations. In both cases the wave functions which are strictly localized at $t=0$, at later times do not vanish {\it outside} the future light cone. \end{abstract} | Quantum Physics (quant-ph) | There are serious errors in the calculations | factual/methodological/other critical errors in manuscript | 14,079 |
2404.10011v4 | Quantum dynamics of the effective field theory of the Calogero-Sutherland model | We consider the known effective field theory of the Calogero-Sutherland model in the thermodynamic limit of large number of particles, obtained from the standard procedure in conformal field theory: the Hilbert space is constructed a priori in terms of irreducible representations of the symmetry algebra, and not by diagonalization of the hamiltonian, which is given in terms of fields that carry representations of the W-infinity algebra (representing the incompressibility of the Fermi sea). Nevertheless, the role of the effective hamiltonian of the theory is to establish a specific dynamics, which deserves further consideration. We show that the time evolution of the (chiral or antichiral) density field is given by the quantum Benjamin-Ono equation, in agreement with previous results obtained from the alternative description of the continuous limit of the model, based on quantum hydrodynamics. In this study, all calculations are performed at the quantum operator level, without making any assumption on the semiclassical limit of the fields and their equations of motion. This result may be considered as a reliable indication of the equivalence between the quantum field theoretic and quantum hydrodynamical formulations of the effective theories of the model. A one-dimensional quantum compressible fluid that includes both chiralities is the physical picture that emerges for the continuous limit of the Calogero-Sutherland model. | High Energy Physics - Theory (hep-th) | Error in revised version. Original is correct | factual/methodological/other critical errors in manuscript | 14,081 |
2404.10085v2 | The Average Spectrum Norm and Near-Optimal Tensor Completion | We introduce a new tensor norm, the average spectrum norm, to study sample complexity of tensor completion problems based on the canonical polyadic decomposition (CPD). Properties of the average spectrum norm and its dual norm are investigated, demonstrating their utility for low-rank tensor recovery analysis. Our novel approach significantly reduces the provable sample rate for CPD-based noisy tensor completion, providing the best bounds to date on the number of observed noisy entries required to produce an arbitrarily accurate estimate of an underlying mean value tensor. Under Poisson and Bernoulli multivariate distributions, we show that an $N$-way CPD rank-$R$ parametric tensor $\boldsymbol{\mathscr{M}}\in\mathbb{R}^{I\times \cdots\times I}$ generating noisy observations can be approximated by large likelihood estimators from $\mathcal{O}(IR^2\log^{N+2}(I))$ revealed entries. Furthermore, under nonnegative and orthogonal versions of the CPD we improve the result to depend linearly on the rank, achieving the near-optimal rate $\mathcal{O}(IR\log^{N+2}(I))$. | Information Theory (cs.IT) | Error, in Section 2.1.2 | factual/methodological/other critical errors in manuscript | 14,082 |
2404.10274v2 | Sparse Attention Regression Network Based Soil Fertility Prediction With Ummaso | The challenge of imbalanced soil nutrient datasets significantly hampers accurate predictions of soil fertility. To tackle this, a new method is suggested in this research, combining Uniform Manifold Approximation and Projection (UMAP) with Least Absolute Shrinkage and Selection Operator (LASSO). The main aim is to counter the impact of uneven data distribution and improve soil fertility models' predictive precision. The model introduced uses Sparse Attention Regression, effectively incorporating pertinent features from the imbalanced dataset. UMAP is utilized initially to reduce data complexity, unveiling hidden structures and important patterns. Following this, LASSO is applied to refine features and enhance the model's interpretability. The experimental outcomes highlight the effectiveness of the UMAP and LASSO hybrid approach. The proposed model achieves outstanding performance metrics, reaching a predictive accuracy of 98%, demonstrating its capability in accurate soil fertility predictions. Additionally, it showcases a Precision of 91.25%, indicating its adeptness in identifying fertile soil instances accurately. The Recall metric stands at 90.90%, emphasizing the model's ability to capture true positive cases effectively. | Artificial Intelligence (cs.AI) | There is an error in the result section | factual/methodological/other critical errors in manuscript | 14,085 |
2404.12678v2 | Exploring Interactive Semantic Alignment for Efficient HOI Detection with Vision-language Model | Human-Object Interaction (HOI) detection aims to localize human-object pairs and comprehend their interactions. Recently, two-stage transformer-based methods have demonstrated competitive performance. However, these methods frequently focus on object appearance features and ignore global contextual information. Besides, vision-language model CLIP which effectively aligns visual and text embeddings has shown great potential in zero-shot HOI detection. Based on the former facts, We introduce a novel HOI detector named ISA-HOI, which extensively leverages knowledge from CLIP, aligning interactive semantics between visual and textual features. We first extract global context of image and local features of object to Improve interaction Features in images (IF). On the other hand, we propose a Verb Semantic Improvement (VSI) module to enhance textual features of verb labels via cross-modal fusion. Ultimately, our method achieves competitive results on the HICO-DET and V-COCO benchmarks with much fewer training epochs, and outperforms the state-of-the-art under zero-shot settings. | Computer Vision and Pattern Recognition (cs.CV) | There are issues with the experimental results | factual/methodological/other critical errors in manuscript | 14,086 |
2404.13374v2 | Exploring Detached Eclipsing Binary Systems from TESS Observations: Insights into OBA-type Systems and Orbital Circularization | This study presents photometric solutions for a carefully selected sample of 181 detached eclipsing binary systems recently observed by the Transiting Exoplanet Survey Satellite (TESS) mission. Our findings contribute to discussions about OBA-type systems and the orbital circularization influenced by tidal interactions. The results encompass crucial parameters, including the sum of radii fraction ($r_{\rm a}\,+\,r_{\rm b}$), radii ratio ($k$), orbital inclination ($i$), surface brightness ratio ($J$), and combinations of the longitude of the periastron and orbital eccentricity ($e\,\sin\,\omega$ and $e\,\cos\,\omega$). Geometric light curve fitting is performed using version 43 of the {\sc jktebop} code, serving as the primary tool for determining orbital elements and physical ratios. Careful uncertainty estimates for these findings are derived through bootstrap simulations. This work introduces unprecedented photometric solutions for 172 well-detached eclipsing systems, while the results for the remaining nine systems exhibit excellent agreement with those previously reported in the literature. Additionally, a critical primary radius fraction ($R_{\rm a}/a$) of 0.266 is identified for our sample of radiative envelope stars, consistent with observational and theoretical findings in the literature. Finally, we determine a circularization period of 5.762 days based on a function from the literature, revealing a discrepancy with Zahn's theory for hot stars. | Solar and Stellar Astrophysics (astro-ph.SR) | When we updated our paper, errors emerged in the figures due to JKTEBOP's limitations with our data. We chose the PHOEBE code, revealing significant discrepancies in results. JKTEBOP's susceptibility to noise also undermines result validity. Thus, we withdrawn the work, recognizing JKTEBOP's inadequacy in our data. Consequently, we have decided to discontinue this line of investigation | factual/methodological/other critical errors in manuscript | 14,089 |
2404.18586v2 | How to surpass no-go limits in Gaussian quantum error correction and entangled Gaussian state distillation? | Gaussian quantum information processing with continuous-variable (CV) quantum information carriers holds significant promise for applications in quantum communication and quantum internet. However, applying Gaussian state distillation and quantum error correction (QEC) faces limitations imposed by no-go results concerning local Gaussian unitary operations and classical communications. This paper introduces a Gaussian QEC protocol that relies solely on local Gaussian resources. A pivotal component of our approach is CV gate teleportation using entangled Gaussian states, which facilitates the implementation of the partial transpose operation on a quantum channel. Consequently, we can efficiently construct a two-mode noise-polarized channel from two noisy Gaussian channels. Furthermore, this QEC protocol naturally extends to a nonlocal Gaussian state distillation protocol. | Quantum Physics (quant-ph) | Lemma 3 and Lemma 4 are incorrect | factual/methodological/other critical errors in manuscript | 14,098 |
2405.00259v2 | Optimization of Dark-Field CT for Lung Imaging | Background: X-ray grating-based dark-field imaging can sense the small angle scattering caused by an object's micro-structure. This technique is sensitive to lung's porous alveoli and is able to detect lung disease at an early stage. Up to now, a human-scale dark-field CT has been built for lung imaging. Purpose: This study aimed to develop a more thorough optimization method for dark-field lung CT and summarize principles for system design. Methods: We proposed a metric in the form of contrast-to-noise ratio (CNR) for system parameter optimization, and designed a phantom with concentric circle shape to fit the task of lung disease detection. Finally, we developed the calculation method of the CNR metric, and analyzed the relation between CNR and system parameters. Results: We showed that with other parameters held constant, the CNR first increases and then decreases with the system auto-correlation length (ACL). The optimal ACL is nearly not influenced by system's visibility, and is only related to phantom's property, i.e., scattering material's size and phantom's absorption. For our phantom, the optimal ACL is about 0.21 {\mu}m. As for system geometry, larger source-detector and isocenter-detector distance can increase the system's maximal ACL, helping the system meet the optimal ACL more easily. Conclusions: This study proposed a more reasonable metric and a task-based process for optimization, and demonstrated that the system optimal ACL is only related to the phantom's property. | Medical Physics (physics.med-ph) | There is a mistake in subsection 2.3, where the content is not correct because of the incorrect parameter we set, which leads to the following calculations in the following sections potentially incorrect | factual/methodological/other critical errors in manuscript | 14,100 |
2405.00618v6 | An axiomatisation of the temporal logic of two dimensional Minkowski spacetime | We define temporal axioms that are sound and complete for the temporal validities over $(\reals^2, <)$. | Logic (math.LO) | A serious problem with the proof was brought to my attention. I hope to repair and re-post at a later date | factual/methodological/other critical errors in manuscript | 14,103 |
2405.00952v2 | Free group of Hamel bijections of big size | A $f\colon\mathbb{R}\to\mathbb{R}$ is called Hamel function if its graph is a Hamel basis of the linear space $\mathbb{R}^2$ over rationals. We construct, assuming CH, a free group of the size $2^\mathfrak{c}$ contained in the class of all Hamel functions, with the indentity function included. This answers, consistently, a question posed recently by M. Lichman, M. Pawlikowski, S. Smolarek, and J. Swaczyna. | Group Theory (math.GR) | The result is false and it can't be corrected | factual/methodological/other critical errors in manuscript | 14,106 |
2405.01133v3 | A missing theorem on dual spaces | We answer in the affirmative the surprisingly difficult questions: If a complex Banach space possesses a real predual X, then is X a complex Banach space? If a complex Banach space possesses a real predual, then does it have a complex predual? We also answer the analogous questions for operator spaces, that is spaces of operators on a Hilbert space, up to complete isometry. Indeed we use operator space methods to solve the Banach space question above. | Functional Analysis (math.FA) | Error in early lemma (Proposition 2.3) endangers Theorem 4.1. Result is valid assuming the conclusions of Proposition 2.3 for the map q in Theorem 4.1 | factual/methodological/other critical errors in manuscript | 14,107 |
2405.03612v2 | Fields of definition of dynamical systems on $\mathbb{P}^{1}$. Improvements on a result of Silverman | J. Silverman proved that a dynamical system on $\mathbb{P}^{1}$ descends to the field of moduli if it is polynomial or it has even degree, but for non-polynomial ones of odd degree the picture is less clear. We give a complete characterization of which dynamical systems over $\mathbb{P}^{1}$ descend to the field of moduli. | Number Theory (math.NT) | There is a mistake in the proof of the main theorem. In the middle of page 5, we state that ϕhas equal orders of vanishing in 0 and \infty. However, the argument only proves the weaker statement that the ramification degrees are equal. This is not sufficient to conclude | factual/methodological/other critical errors in manuscript | 14,110 |
2405.04269v2 | An Analysis of Sea Level Spatial Variability by Topological Indicators and $k$-means Clustering Algorithm | The time-series data of sea level rise and fall contains crucial information on the variability of sea level patterns. Traditional $k$-means clustering is commonly used for categorizing regional variability of sea level, however, its results are not robust against a number of factors. This study analyzed fourteen datasets of monthly sea level in fourteen shoreline regions of Peninsular Malaysia. We applied a hybridization of clustering technique to analyze data categorization and topological data analysis method to enhance the performance of our clustering analysis. Specifically, our approach utilized the persistent homology and $k$-means/$k$-means++ clustering. The fourteen data sets from fourteen tide gauge stations were categorized in classes based on a prior categorization that was determined by topological information, and the probability of data points that belong to certain groups that is yielded by $k$-means/$k$-means++ clustering. Our results demonstrated that our method significantly improves the performance of traditional clustering techniques. | Applications (stat.AP) | There are some mistakes in the submission, and it needs major revision | factual/methodological/other critical errors in manuscript | 14,112 |
2405.05635v2 | Large Bricks and Join-irreducible torsionfree classes | We show that every join-irreducible torsionfree class in the category of finitely generated modules over an artinian ring is cogenerated by a single (not necessarily finitely generated) brick. This is a partial extension of the characterisation of completely join-irreducible torsionfree classes given by Barnard, Carroll and Zhu. | Representation Theory (math.RT) | Found a gap in the proof of Proposition 3.9 | factual/methodological/other critical errors in manuscript | 14,113 |
2405.07197v2 | Qsyn: A Developer-Friendly Quantum Circuit Synthesis Framework for NISQ Era and Beyond | In this paper, we introduce a new quantum circuit synthesis (QCS) framework, Qsyn, for developers to research, develop, test, experiment, and then contribute their QCS algorithms and tools to the framework. Our framework is more developer-friendly than other modern QCS frameworks in three aspects: (1) We design a rich command-line interface so that developers can easily design various testing scenarios and flexibly conduct experiments on their algorithms. (2) We offer detailed access to many data representations on different abstract levels of quantum circuits so that developers can optimize their algorithms to the extreme. (3) We define a rigid developing flow and environment so that developers can ensure their development qualities with the best modern software engineering practices. We illustrate the friendliness of our framework with a showcase of developing a T-Count Optimization algorithm and demonstrate our performance superiority with fair comparisons to other modern QCS frameworks. | Quantum Physics (quant-ph) | Table II has errors in parts of its data and needs to be revised | factual/methodological/other critical errors in manuscript | 14,119 |
2405.07257v2 | Listen, Disentangle, and Control: Controllable Speech-Driven Talking Head Generation | Most earlier investigations on talking face generation have focused on the synchronization of lip motion and speech content. However, human head pose and facial emotions are equally important characteristics of natural human faces. While audio-driven talking face generation has seen notable advancements, existing methods either overlook facial emotions or are limited to specific individuals and cannot be applied to arbitrary subjects. In this paper, we propose a one-shot Talking Head Generation framework (SPEAK) that distinguishes itself from general Talking Face Generation by enabling emotional and postural control. Specifically, we introduce the Inter-Reconstructed Feature Disentanglement (IRFD) method to decouple human facial features into three latent spaces. We then design a face editing module that modifies speech content and facial latent codes into a single latent space. Subsequently, we present a novel generator that employs modified latent codes derived from the editing module to regulate emotional expression, head poses, and speech content in synthesizing facial animations. Extensive trials demonstrate that our method can generate realistic talking head with coordinated lip motions, authentic facial emotions, and smooth head movements. The demo video is available at the anonymous link: this https URL | Computer Vision and Pattern Recognition (cs.CV) | Due to our negligence, there are factual errors in the experimental results, so we are considering resubmitting the paper after an overhaul | factual/methodological/other critical errors in manuscript | 14,120 |
2405.07292v2 | Kernel Three Pass Regression Filter | We forecast a single time series using a high-dimensional set of predictors. When these predictors share common underlying dynamics, an approximate latent factor model provides a powerful characterization of their co-movements Bai(2003). These latent factors succinctly summarize the data and can also be used for prediction, alleviating the curse of dimensionality in high-dimensional prediction exercises, see Stock & Watson (2002a). However, forecasting using these latent factors suffers from two potential drawbacks. First, not all pervasive factors among the set of predictors may be relevant, and using all of them can lead to inefficient forecasts. The second shortcoming is the assumption of linear dependence of predictors on the underlying factors. The first issue can be addressed by using some form of supervision, which leads to the omission of irrelevant information. One example is the three-pass regression filter proposed by Kelly & Pruitt (2015). We extend their framework to cases where the form of dependence might be nonlinear by developing a new estimator, which we refer to as the Kernel Three-Pass Regression Filter (K3PRF). This alleviates the aforementioned second shortcoming. The estimator is computationally efficient and performs well empirically. The short-term performance matches or exceeds that of established models, while the long-term performance shows significant improvement. | Econometrics (econ.EM) | We have identified some errors and are currently improving them. So we do not want people to read erroneous paper | factual/methodological/other critical errors in manuscript | 14,121 |
2405.07736v2 | Learning to Plan Maneuverable and Agile Flight Trajectory with Optimization Embedded Networks | In recent times, an increasing number of researchers have been devoted to utilizing deep neural networks for end-to-end flight navigation. This approach has gained traction due to its ability to bridge the gap between perception and planning that exists in traditional methods, thereby eliminating delays between modules. However, the practice of replacing original modules with neural networks in a black-box manner diminishes the overall system's robustness and stability. It lacks principled explanations and often fails to consistently generate high-quality motion trajectories. Furthermore, such methods often struggle to rigorously account for the robot's kinematic constraints, resulting in the generation of trajectories that cannot be executed satisfactorily. In this work, we combine the advantages of traditional methods and neural networks by proposing an optimization-embedded neural network. This network can learn high-quality trajectories directly from visual inputs without the need of mapping, while ensuring dynamic feasibility. Here, the deep neural network is employed to directly extract environment safety regions from depth images. Subsequently, we employ a model-based approach to represent these regions as safety constraints in trajectory optimization. Leveraging the availability of highly efficient optimization algorithms, our method robustly converges to feasible and optimal solutions that satisfy various user-defined constraints. Moreover, we differentiate the optimization process, allowing it to be trained as a layer within the neural network. This approach facilitates the direct interaction between perception and planning, enabling the network to focus more on the spatial regions where optimal solutions exist. As a result, it further enhances the quality and stability of the generated trajectories. | Robotics (cs.RO) | Some statements in the introduction may be controversial | factual/methodological/other critical errors in manuscript | 14,123 |
2405.08386v3 | Robust non-Abelian even-denominator fractional Chern insulator in twisted bilayer MoTe$_2$ | A recent experiment observes a series of quantum Hall effects in transition metal dichalcogenide moiré MoTe$_2$ [K. Kang, et. al, Nature 628, 522-526 (2024)]. Among them, the filling $\nu$ = 3 state points to a time-reversal pair of edge states resembling those of the even-denominator fractional Chern insulators (FCI). Inspired by this discovery, we investigate whether a robust incompressible quantum Hall liquid can be stabilized in the half-filled Chern band of twisted MoTe$_2$ bilayers. We use the continuum model with parameters relevant to twisted MoTe$_2$ bilayers and obtain three consecutive nearly flat Chern bands that resemble the experimental plateaus at filling $\nu$ = 2, 4, 6. Crucially, when the second moiré miniband is half-filled, signatures of non-Abelian states are found via exact diagonalization calculations, including the stable six-fold ground state degeneracy which grows more robust for larger lattice sizes in consistency with an even-denominator FCI state. We further perform flux insertion simulations to reveal a 1/2 quantized many-body Chern number. Furthermore, the ground state density structure factors show no sharp peak, which excludes the charge density wave order. These evidences signal the potential of realizing the non-Abelian state at zero magnetic field in twisted MoTe$_2$ bilayers at the fractional hole filling 3/2. | Strongly Correlated Electrons (cond-mat.str-el) | Error in data | factual/methodological/other critical errors in manuscript | 14,125 |
2405.10329v2 | Causal inference approach to appraise long-term effects of maintenance policy on functional performance of asphalt pavements | Asphalt pavements as the most prevalent transportation infrastructure, are prone to serious traffic safety problems due to functional or structural damage caused by stresses or strains imposed through repeated traffic loads and continuous climatic cycles. The good quality or high serviceability of infrastructure networks is vital to the urbanization and industrial development of nations. In order to maintain good functional pavement performance and extend the service life of asphalt pavements, the long-term performance of pavements under maintenance policies needs to be evaluated and favorable options selected based on the condition of the pavement. A major challenge in evaluating maintenance policies is to produce valid treatments for the outcome assessment under the control of uncertainty of vehicle loads and the disturbance of freeze-thaw cycles in the climatic environment. In this study, a novel causal inference approach combining a classical causal structural model and a potential outcome model framework is proposed to appraise the long-term effects of four preventive maintenance treatments for longitudinal cracking over a 5-year period of upkeep. Three fundamental issues were brought to our attention: 1) detection of causal relationships prior to variables under environmental loading (identification of causal structure); 2) obtaining direct causal effects of treatment on outcomes excluding covariates (identification of causal effects); and 3) sensitivity analysis of causal relationships. The results show that the method can accurately evaluate the effect of preventive maintenance treatments and assess the maintenance time to cater well for the functional performance of different preventive maintenance approaches. This framework could help policymakers to develop appropriate maintenance strategies for pavements. | Applications (stat.AP) | The arXiv version needs to be withdrawn since the model needs to be validated and updated with advanced machine learning technologies to enhance the accuracy, and there are some crucial definition errors of symbols in the arXiv version | factual/methodological/other critical errors in manuscript | 14,130 |
2405.11165v2 | Automated Multi-level Preference for MLLMs | Current multimodal Large Language Models (MLLMs) suffer from "hallucination", occasionally generating responses that are not grounded in the input images. To tackle this challenge, one promising path is to utilize reinforcement learning from human feedback (RLHF), which steers MLLMs towards learning superior responses while avoiding inferior ones. We rethink the common practice of using binary preferences (i.e., superior, inferior), and find that adopting multi-level preferences (e.g., superior, medium, inferior) is better for two benefits: 1) It narrows the gap between adjacent levels, thereby encouraging MLLMs to discern subtle differences. 2) It further integrates cross-level comparisons (beyond adjacent-level comparisons), thus providing a broader range of comparisons with hallucination examples. To verify our viewpoint, we present the Automated Multi-level Preference (\textbf{AMP}) framework for MLLMs. To facilitate this framework, we first develop an automated dataset generation pipeline that provides high-quality multi-level preference datasets without any human annotators. Furthermore, we design the Multi-level Direct Preference Optimization (MDPO) algorithm to robustly conduct complex multi-level preference learning. Additionally, we propose a new hallucination benchmark, MRHal-Bench. Extensive experiments across public hallucination and general benchmarks, as well as our MRHal-Bench, demonstrate the effectiveness of our proposed method. | Computer Vision and Pattern Recognition (cs.CV) | Some results of comparison study on mmhal-bench and mrhal-bench are revised. We also revised some details of MRHal-Bench, including quantity, categories, etc. Besides, some symbols are inconsistent. All these things will mislead readers. Therefore, we apply for this withdrawal | factual/methodological/other critical errors in manuscript | 14,132 |
2405.11232v2 | Multiplication formula for Hernandez and Leclerc's quivers with potentials | In this paper, we study multiplication formula of $F$-polynomial of representations of Hernandez and Leclerc's quivers with potentials. Since the truncated $q$-characters of some real simple modules over a quantum affine group $U_q(\widehat{\mathfrak{g}})$ can be expressed in terms of such $F$-polynomials, one can describe the product of two simple modules over $U_q(\widehat{\mathfrak{g}})$ using this multiplication formula. | Representation Theory (math.RT) | There is an error: In section 2. Jacobian algebras do in general NOT enjoy the Ext-symmetry which was crucial for the GLS multiplication formula. Morevor, the generalized preprojective are in general NOT Jacobian algebras because the nilpotency relations of the loops don't come from the potential | factual/methodological/other critical errors in manuscript | 14,133 |
2405.11537v2 | VR-GPT: Visual Language Model for Intelligent Virtual Reality Applications | The advent of immersive Virtual Reality applications has transformed various domains, yet their integration with advanced artificial intelligence technologies like Visual Language Models remains underexplored. This study introduces a pioneering approach utilizing VLMs within VR environments to enhance user interaction and task efficiency. Leveraging the Unity engine and a custom-developed VLM, our system facilitates real-time, intuitive user interactions through natural language processing, without relying on visual text instructions. The incorporation of speech-to-text and text-to-speech technologies allows for seamless communication between the user and the VLM, enabling the system to guide users through complex tasks effectively. Preliminary experimental results indicate that utilizing VLMs not only reduces task completion times but also improves user comfort and task engagement compared to traditional VR interaction methods. | Robotics (cs.RO) | The paper was not accepted for the conference. It has a large amount of errors, both factological and grammatical. Moreover, new idea is being developed based on the technology by our research group. New paper will be submitted soon. The withdrawal request is made in order to not misguide other scientists on the technology and to preserve the name | factual/methodological/other critical errors in manuscript | 14,134 |
2405.12710v3 | Text-Video Retrieval with Global-Local Semantic Consistent Learning | Adapting large-scale image-text pre-training models, e.g., CLIP, to the video domain represents the current state-of-the-art for text-video retrieval. The primary approaches involve transferring text-video pairs to a common embedding space and leveraging cross-modal interactions on specific entities for semantic alignment. Though effective, these paradigms entail prohibitive computational costs, leading to inefficient retrieval. To address this, we propose a simple yet effective method, Global-Local Semantic Consistent Learning (GLSCL), which capitalizes on latent shared semantics across modalities for text-video retrieval. Specifically, we introduce a parameter-free global interaction module to explore coarse-grained alignment. Then, we devise a shared local interaction module that employs several learnable queries to capture latent semantic concepts for learning fine-grained alignment. Furthermore, an Inter-Consistency Loss (ICL) is devised to accomplish the concept alignment between the visual query and corresponding textual query, and an Intra-Diversity Loss (IDL) is developed to repulse the distribution within visual (textual) queries to generate more discriminative concepts. Extensive experiments on five widely used benchmarks (i.e., MSR-VTT, MSVD, DiDeMo, LSMDC, and ActivityNet) substantiate the superior effectiveness and efficiency of the proposed method. Remarkably, our method achieves comparable performance with SOTA as well as being nearly 220 times faster in terms of computational cost. Code is available at: this https URL . | Computer Vision and Pattern Recognition (cs.CV) | The author has withdrawn this paper due to a critical definitional error in concept learning for global/local-interaction learning during training. This error led to an alignment issue with the definition of the text-video retrieval task, causing an unfair comparison with state-of-the-art (SOTA) methods. Consequently, this hindered the accurate evaluation of the paper's contributions | factual/methodological/other critical errors in manuscript | 14,136 |
2405.13300v3 | FAITH: Frequency-domain Attention In Two Horizons for Time Series Forecasting | Time Series Forecasting plays a crucial role in various fields such as industrial equipment maintenance, meteorology, energy consumption, traffic flow and financial investment. However, despite their considerable advantages over traditional statistical approaches, current deep learning-based predictive models often exhibit a significant deviation between their forecasting outcomes and the ground truth. This discrepancy is largely due to an insufficient emphasis on extracting the sequence's latent information, particularly its global information within the frequency domain and the relationship between different variables. To address this issue, we propose a novel model Frequency-domain Attention In Two Horizons, which decomposes time series into trend and seasonal components using a multi-scale sequence adaptive decomposition and fusion architecture, and processes them separately. FAITH utilizes Frequency Channel feature Extraction Module and Frequency Temporal feature Extraction Module to capture inter-channel relationships and temporal global information in the sequence, significantly improving its ability to handle long-term dependencies and complex patterns. Furthermore, FAITH achieves theoretically linear complexity by modifying the time-frequency domain transformation method, effectively reducing computational costs. Extensive experiments on 6 benchmarks for long-term forecasting and 3 benchmarks for short-term forecasting demonstrate that FAITH outperforms existing models in many fields, such as electricity, weather and traffic, proving its effectiveness and superiority both in long-term and short-term time series forecasting tasks. Our codes and data are available at this https URL . | Machine Learning (cs.LG) | We think there are some errors in the experiment result, it may lead to a wrong conclusion. So we think it will be responsible to withdraw it | factual/methodological/other critical errors in manuscript | 14,138 |
2405.15377v2 | Dynamic Planning for Sequential Whole-body Mobile Manipulation | The dynamic Sequential Mobile Manipulation Planning (SMMP) framework is essential for the safe and robust operation of mobile manipulators in dynamic environments. Previous research has primarily focused on either motion-level or task-level dynamic planning, with limitations in handling state changes that have long-term effects or in generating responsive motions for diverse tasks, respectively. This paper presents a holistic dynamic planning framework that extends the Virtual Kinematic Chain (VKC)-based SMMP method, automating dynamic long-term task planning and reactive whole-body motion generation for SMMP problems. The framework consists of an online task planning module designed to respond to environment changes with long-term effects, a VKC-based whole-body motion planning module for manipulating both rigid and articulated objects, alongside a reactive Model Predictive Control (MPC) module for obstacle avoidance during execution. Simulations and real-world experiments validate the framework, demonstrating its efficacy and validity across sequential mobile manipulation tasks, even in scenarios involving human interference. | Robotics (cs.RO) | technical issue | factual/methodological/other critical errors in manuscript | 14,141 |
2405.16078v2 | An Multi-resources Integration Empowered Task Offloading in Internet of Vehicles: From the Perspective of Wireless Interference | The task offloading technology plays a vital role in the Internet of Vehicles (IoV), by satisfying the diversified demands of the vehicles, such as the energy consumption and processing latency of the computing task. Different from the previous works, on the one hand, they ignored the wireless interference of communications among vehicle-to-vehicle (V2V), as well as between vehicles and roadside units (RSU); on the other hand, the available resources of parked vehicles on the roadside and other moving vehicles on the road are also ignored. In this paper, first of all, we adopt a truncated Gaussian distribution for modeling the vehicle moving speed, instead of the simplistic average speed models in prior studies. Then, with the consideration of wireless interference and effective communication duration existing in V2V and RSUs, we establish an analytical framework of the task offloading, characterized by the energy consumption and processing delay, by integrating computing resources of parked/moving vehicles and RSUs. Furthermore, inspired by the method of multi-agent deterministic policy gradient (MADDPG), we address a joint optimization of the energy consumption and processing delay of the computing task, while ensuring the load balancing of the resources. Finally, the simulations demonstrate the effectiveness and correctness of the proposed MADDPG. In particular, compared with the current popular methods of the task offloading, the MADDPG shows the best performance, in terms of convergence speed, energy consumption and processing delay. | Information Theory (cs.IT) | The paper has been rejected by IEEE Transactions on Communications, apart from the Reviewers' comments, we need reconsider that inaccuracies in the data or results were identified post-submission, necessitating a withdrawal for correction. In addition, considering the plausibility of the simulations, one or more of the authors requested the withdrawal of the manuscript | factual/methodological/other critical errors in manuscript | 14,142 |
2405.20105v2 | The first superconducting final focus quadrupole prototype of the FCC-ee study | A single aperture Canted-Cosine-Theta (CCT) quadrupole magnet, made of NbTi superconductors, has been developed for the final focus region of the FCC-ee study. The conductor layout is optimised to mitigate edge effects on one of the two sides of the magnet that typically lead to undesired higher-order multipoles. Experimental results of a prototype, including paraffin wax impregnation and cryogenic temperature measurements, are presented. The magnet exhibits no training behaviour, surpassing the nominal current during the initial ramp. Field quality is excellent, with higher-order multipoles below $1\times 10^{-4}$ units, consistent with simulations and room temperature tests. These findings confirm the potential of superconducting CCT magnets to offer compact solutions for applications demanding stringent field quality. | Accelerator Physics (physics.acc-ph) | There were multiple errors in the values of Table 2 | factual/methodological/other critical errors in manuscript | 14,144 |
2405.20528v4 | On the Convergence of the Sinkhorn-Knopp Algorithm with Sparse Cost Matrices | Matrix scaling problems with sparse cost matrices arise frequently in various domains, such as optimal transport, image processing, and machine learning. The Sinkhorn-Knopp algorithm is a popular iterative method for solving these problems, but its convergence properties in the presence of sparsity have not been thoroughly analyzed. This paper presents a theoretical analysis of the convergence rate of the Sinkhorn-Knopp algorithm specifically for sparse cost matrices. We derive novel bounds on the convergence rate that explicitly depend on the sparsity pattern and the degree of nonsparsity of the cost matrix. These bounds provide new insights into the behavior of the algorithm and highlight the potential for exploiting sparsity to develop more efficient solvers. We also explore connections between our sparse convergence results and existing convergence results for dense matrices, showing that our bounds generalize the dense case. Our analysis reveals that the convergence rate improves as the matrix becomes less sparse and as the minimum entry of the cost matrix increases relative to its maximum entry. These findings have important practical implications, suggesting that the Sinkhorn-Knopp algorithm may be particularly well-suited for large-scale matrix scaling problems with sparse cost matrices arising in real-world applications. Future research directions include investigating tighter bounds based on more sophisticated sparsity patterns, developing algorithm variants that actively exploit sparsity, and empirically validating the benefits of our theoretical results on real-world datasets. This work advances our understanding of the Sinkhorn-Knopp algorithm for an important class of matrix scaling problems and lays the foundation for designing more efficient and scalable solutions in practice. | Optimization and Control (math.OC) | [REDACTED-NAME] Theorem | factual/methodological/other critical errors in manuscript | 14,145 |
2405.20571v2 | On the principal eigenvalue for compound Poisson processes | We investigate the explicit expression for the principal eigenvalue $\lambda_{1}^{X}(D)$ for a large class of compound Poisson processes $X$ on a bounded open set $D$ by examining its spectral heat content. When the jump density of the compound Poisson process is radially symmetric and strictly decreasing, we demonstrate that balls are the unique minimizers for $\lambda_{1}^{X}(D)$ among all sets with equal Lebesgue measure. Furthermore, we show that this uniqueness fails if the jump density is not strictly decreasing. | Probability (math.PR) | There is a critical flaw in the proof and the main theorem, Theorem 2.1, is not true in the stated form | factual/methodological/other critical errors in manuscript | 14,146 |
2406.00665v2 | Integrating solid direct air capture systems with green hydrogen production: Economic synergy of sector coupling | In the global pursuit of sustainable energy solutions, mitigating carbon dioxide (CO2) emissions stands as a pivotal challenge. With escalating atmospheric CO2 levels, the imperative of direct air capture (DAC) systems becomes evident. Simultaneously, green hydrogen (GH) emerges as a pivotal medium for renewable energy. Nevertheless, the substantial expenses associated with these technologies impede widespread adoption, primarily due to significant installation costs and underutilized operational advantages when deployed independently. Integration through sector coupling enhances system efficiency and sustainability, while shared power sources and energy storage devices offer additional economic benefits. In this study, we assess the economic viability of polymer electrolyte membrane electrolyzers versus alkaline electrolyzers within the context of sector coupling. Our findings indicate that combining GH production with solid DAC systems yields significant economic advantages, with approximately a 10% improvement for PEM electrolyzers and a 20% enhancement for alkaline electrolyzers. These results highlight a substantial opportunity to improve the efficiency and economic viability of renewable energy and green hydrogen initiatives, thereby facilitating the broader adoption of cleaner technologies. | General Economics (econ.GN) | Some of the results of our previous preprint paper are flawed, and we are withdrawing them to prevent the spread of incorrect knowledge | factual/methodological/other critical errors in manuscript | 14,147 |
2406.00801v2 | Ensemble Deep Random Vector Functional Link Neural Network Based on Fuzzy Inference System | The ensemble deep random vector functional link (edRVFL) neural network has demonstrated the ability to address the limitations of conventional artificial neural networks. However, since edRVFL generates features for its hidden layers through random projection, it can potentially lose intricate features or fail to capture certain non-linear features in its base models (hidden layers). To enhance the feature learning capabilities of edRVFL, we propose a novel edRVFL based on fuzzy inference system (edRVFL-FIS). The proposed edRVFL-FIS leverages the capabilities of two emerging domains, namely deep learning and ensemble approaches, with the intrinsic IF-THEN properties of fuzzy inference system (FIS) and produces rich feature representation to train the ensemble model. Each base model of the proposed edRVFL-FIS encompasses two key feature augmentation components: a) unsupervised fuzzy layer features and b) supervised defuzzified features. The edRVFL-FIS model incorporates diverse clustering methods (R-means, K-means, Fuzzy C-means) to establish fuzzy layer rules, resulting in three model variations (edRVFL-FIS-R, edRVFL-FIS-K, edRVFL-FIS-C) with distinct fuzzified features and defuzzified features. Within the framework of edRVFL-FIS, each base model utilizes the original, hidden layer and defuzzified features to make predictions. Experimental results, statistical tests, discussions and analyses conducted across UCI and NDC datasets consistently demonstrate the superior performance of all variations of the proposed edRVFL-FIS model over baseline models. The source codes of the proposed models are available at this https URL . | Machine Learning (cs.LG) | The numerical experiments have some error | factual/methodological/other critical errors in manuscript | 14,148 |
2406.01892v2 | On the triviality of the unramified Iwasawa modules of the maximal multiple $\mathbb{Z}_p$-extensions | For a number field $k$ and an odd prime number $p$, we consider the maximal multiple $\mathbb{Z}_p$-extension $\tilde{k}$ of $k$ and the unramified Iwasawa module $X(\tilde{k})$, which is the Galois group of the maximal unramified abelian $p$-extension over $\tilde{k}$. In the present article, we classify CM-fields $k$ which are decomposed completely at $p$ such that $X(\tilde{k})=0$. | Number Theory (math.NT) | A mistake is found in Section 4.2.3 | factual/methodological/other critical errors in manuscript | 14,150 |
2406.02169v2 | A multilingual dataset for offensive language and hate speech detection for hausa, yoruba and igbo languages | The proliferation of online offensive language necessitates the development of effective detection mechanisms, especially in multilingual contexts. This study addresses the challenge by developing and introducing novel datasets for offensive language detection in three major Nigerian languages: Hausa, Yoruba, and Igbo. We collected data from Twitter and manually annotated it to create datasets for each of the three languages, using native speakers. We used pre-trained language models to evaluate their efficacy in detecting offensive language in our datasets. The best-performing model achieved an accuracy of 90\%. To further support research in offensive language detection, we plan to make the dataset and our models publicly available. | Computation and Language (cs.CL) | The experimental result was erroneously reported and we also omitted other authors | factual/methodological/other critical errors in manuscript | 14,151 |
2406.02713v2 | On rectangular Toda brackets and Oda's extension problems | This paper tackles \textit{N. Oda}'s extension problems for the homotopy groups $\pi_{39}(S^{6})$, $\pi_{40}(S^{7})$, and $\pi_{41}(S^{8})$ localized at 2, the issues having eluded resolution for more than four decades. We introduce a tool for the theory of determinations of unstable homotopy groups, namely, the rectangular Toda bracket, by which we are able to solve the extension problems with respect to these three homotopy groups. | Algebraic Topology (math.AT) | There are native errors on the def. of my rectangular Toda brackets | factual/methodological/other critical errors in manuscript | 14,152 |
2406.03201v2 | Characteristic ideal of the fine Selmer group and results on $μ$-invariance under isogeny in the function field case | Consider a function field $K$ with characteristic $p>0$. We investigate the $\Lambda$-module structure of the Mordell-Weil group of an abelian variety over $\mathbb{Z}_p$-extensions of $K$, generalizing results due to Lee. Next, we study the algebraic structure and prove a control theorem for the S-fine Mordell-Weil groups, the function field analogue for Wuthrich's fine Mordell-Weil groups, over a $\mathbb{Z}_p$-extension of $K$. In case of unramified $\mathbb{Z}_p$-extension, $K_\infty$, we compute the characteristic ideal of the Pontryagin dual of the S-fine Mordell group. This provides an answer to an analogue of Greenberg's question for the characteristic ideal of the dual fine Selmer group in the function field setup. In the $\ell\neq p$ case, we prove the triviality of the $\mu$-invariant for the Selmer group (same as the fine Selmer group in this case) of an elliptic curve over a non-commutative $GL_2(\mathbb{Z}_\ell)$-extension of $K$ and thus extending Conjecture A. In the $\ell=p$ case, we compute the change of $\mu$-invariants of the dual Selmer groups of elliptic curves under isogeny, giving a lower bound for the $\mu$-invariant. | Number Theory (math.NT) | There is an error in the proof of Proposition 4.6 (and hence Theorem 4.9). This is corrected in arXiv:2408.06938. There is also an error in the proof of Theorem 5.1. This is corrected in a separate paper (arxiv: 2407.21431). The results in section 6, although minor, are ok | factual/methodological/other critical errors in manuscript | 14,154 |
2406.04846v2 | Efficient Fault-Tolerant Single Qubit Gate Approximation And Universal Quantum Computation Without Using The Solovay-Kitaev Theorem | Arbitrarily accurate fault-tolerant (FT) universal quantum computation can be carried out using the Clifford gates Z, S, CNOT plus the non-Clifford T gate. Moreover, a recent improvement of the Solovay-Kitaev theorem by Kuperberg implies that to approximate any single-qubit gate to an accuracy of $\epsilon > 0$ requires $\text{O}(\log^c[1/\epsilon])$ quantum gates with $c > 1.44042$. Can one do better? That was the question asked by Nielsen and Chuang in their quantum computation textbook. Specifically, they posted a challenge to efficiently approximate single-qubit gate, fault-tolerantly or otherwise, using $\Omega(\log[1/\epsilon])$ gates chosen from a finite set. Here I give a partial answer to this question by showing that this is possible using $\text{O}(\log[1/\epsilon] \log\log[1/\epsilon] \log\log\log[1/\epsilon] \cdots)$ FT gates chosen from a finite set depending on the value of $\epsilon$. The key idea is to construct an approximation of any phase gate in a FT way by recursion to any given accuracy $\epsilon > 0$. This method is straightforward to implement, easy to understand, and interestingly does not involve the Solovay-Kitaev theorem. | Quantum Physics (quant-ph) | The claim in this manuscript is incorrect due to a mistake in Eq. (6). The reason is that expression in Eq. (6) is derived in real arithmetic. It is incompatible with the modulo 2 arithmetic in the state ket | factual/methodological/other critical errors in manuscript | 14,158 |
2406.06117v3 | Exclusion of the Cosmological Triangle in Reactor-Based Search for Axion-Like Particles | We report new constraints on axion-like particle (ALP) using data corresponding to a sodium iodine target exposure of 3063 kg$\cdot$days from the neutrino elastic scattering observation with NaI (NEON) experiment. A 16.7 kg of thallium-doped sodium iodide target was located 23.7 meters from a 2.8 GW thermal power nuclear reactor. We searched for ALPs produced by high-flux photons by comparing the energy spectra of data collected during reactor-on (1596 kg$\cdot$days exposure) and reactor-off (1467 kg$\cdot$days exposure) periods. No signal consistent with ALP interaction was identified, allowing us to set exclusion limits at the 95% confidence level. Our limits cover previously unexplored regions for both photon couplings (${g_{a\gamma}}$) and electron couplings (${g_{ae}}$) for axion masses around 1 MeV/c$^2$. Notably, the NEON data excludes the unconstrained region identified by laboratory-based searches for photon couplings within the "cosmological triangle" for the first time. The observed 95\% confidence level limits reach as low as ${g_{a\gamma}}$ of 4.33$\times$ 10$^{-8}$ GeV$^{-1}$ and ${g_{ae}}$ of 1.10$\times$ 10$^{-9}$ for axion masses of 1.7 MeV/c$^2$ and 1.0 MeV/c$^2$, respectively. | High Energy Physics - Experiment (hep-ex) | We have discovered a mistake in the ALP signal generation that artificially enhances our sensitivity. As we need additional time to resolve and update these results, we would like to withdraw this article to avoid any confusion for the readers | factual/methodological/other critical errors in manuscript | 14,160 |
2406.06431v2 | CR functions at CR singularities: approximation, extension, and hulls | We study three possible definitions of the notion of CR functions at CR singular points, their extension to a fixed-neighborhood of the singular point, and analogues of the Baouendi-Tréves approximation in a fixed neighborhood. In particular, given the existence of a large enough disc hull shrinking to a point, we find the fixed-neighborhood extension and hence approximation properties. We provide examples showing the distinctions between the classes and the various properties studied. | Complex Variables (math.CV) | The proof of Theorem 4.2 has a gap. | factual/methodological/other critical errors in manuscript | 14,161 |
2406.06717v2 | Analyzing user archetypes in Singapore's Telegram groups on COVID-19 and climate change | Social media platforms, particularly Telegram, play a pivotal role in shaping public perceptions and opinions on global and national issues. Unlike traditional news media, Telegram allows for the proliferation of user-generated content with minimal oversight, making it a significant venue for the spread of controversial and misinformative content. During the COVID-19 pandemic, Telegram's popularity surged in Singapore, a country with one of the highest rates of social media use globally. We leverage Singapore-based Telegram data to analyze information flows within groups focused on COVID-19 and climate change. Using k-means clustering, we identified distinct user archetypes, including Skeptic, Engaged Advocate, Observer, and Analyst, each contributing uniquely to the discourse. We developed a model to classify users into these clusters (Precision: Climate change: 0.99; COVID-19: 0.95). By identifying these user archetypes and examining their contributions to information dissemination, we sought to uncover patterns to inform effective strategies for combating misinformation and enhancing public discourse on pressing global issues. | Social and Information Networks (cs.SI) | Incomplete data and modification in data analysis | factual/methodological/other critical errors in manuscript | 14,162 |
2406.07682v2 | Stabilization of a Quadrotor via Energy Shaping | Stabilization of a quadrotor without a controller based on cascade structure is a challenging problem. Besides, due to the dynamics and the number of underactuation, an energy shaping controller has not been designed in 3D for a quadrotor. This paper presents a novel solution to the potential energy shaping problem for a quadrotor utilizing the Interconnection and Damping Assignment Passivity Based Control (IDA-PBC) approach. For the first time, we extend the solution of PDEs from the 2D case to the full 3D scenario. This advancement seems to be a significant step forward for stabilization of underactuated aerial vehicles without a cascade controller. The results are verified via simulation on a typical quadrotor. | Systems and Control (eess.SY) | Simulation results are not confirmed by first author | factual/methodological/other critical errors in manuscript | 14,165 |
2406.08777v2 | Finite Time Blowup of Integer- and Fractional-Order Time-Delayed Diffusion Equations | In this work, exact solutions are derived for an integer- and fractional-order time-delayed diffusion equation with arbitrary initial conditions. The solutions are obtained using Fourier transform methods in conjunction with the known properties of delay functions. It is observed that the solutions do not exhibit infinite speed of propagation for smooth initial conditions that are bounded and positive. Sufficient conditions on the initial condition are also established such that the finite time blowup of the solutions can be explicitly calculated. Examples are provided that highlight the contrasting behaviours of these exact solutions with the known dynamics of solutions to the standard diffusion equation. | Analysis of PDEs (math.AP) | Errors were discovered in the analysis, significant revisions are being made to the manuscript | factual/methodological/other critical errors in manuscript | 14,167 |
2406.08782v2 | Hybrid Spatial-spectral Neural Network for Hyperspectral Image Denoising | Hyperspectral image (HSI) denoising is an essential procedure for HSI applications. Unfortunately, the existing Transformer-based methods mainly focus on non-local modeling, neglecting the importance of locality in image denoising. Moreover, deep learning methods employ complex spectral learning mechanisms, thus introducing large computation costs. To address these problems, we propose a hybrid spatial-spectral denoising network (HSSD), in which we design a novel hybrid dual-path network inspired by CNN and Transformer characteristics, leading to capturing both local and non-local spatial details while suppressing noise efficiently. Furthermore, to reduce computational complexity, we adopt a simple but effective decoupling strategy that disentangles the learning of space and spectral channels, where multilayer perception with few parameters is utilized to learn the global correlations among spectra. The synthetic and real experiments demonstrate that our proposed method outperforms state-of-the-art methods on spatial and spectral reconstruction. The code and details are available on this https URL . | Image and Video Processing (eess.IV) | There are some errors in professional theory | factual/methodological/other critical errors in manuscript | 14,168 |
2406.11623v4 | Nevanlinna Theory on Geodesic Balls of Complete Kähler Manifolds | We study Nevanlinna theory of meromorphic mappings from a geodesic ball of a general complete Kähler manifold with non-negative Ricci curvature into a complex projective manifold by introducing a heat kernel method. When dimension of a target manifold is not greater than one of a source manifold, we establish a second main theorem which is a generalization of the classical second main theorem for a ball of $\mathbb C^m.$ If a source manifold is non-compact and it carries a positive global Green function, then we establish a global second main theorem for the source manifold. As a result, we obtain a Picard's theorem for complete Kähler manifolds with non-negative Ricci curvature. | Complex Variables (math.CV) | Some errors appeared in the article that seem difficult to correct. For example, the Green function $G_R(o,x)$ for the geodesic ball $B(R)$ was misunderstood to satisfy the Dirichlet boundary condition on the geodesic sphere $\partial B(R)$, however, this is not the case | factual/methodological/other critical errors in manuscript | 14,174 |
2406.11802v2 | PhyBench: A Physical Commonsense Benchmark for Evaluating Text-to-Image Models | Text-to-image (T2I) models have made substantial progress in generating images from textual prompts. However, they frequently fail to produce images consistent with physical commonsense, a vital capability for applications in world simulation and everyday tasks. Current T2I evaluation benchmarks focus on metrics such as accuracy, bias, and safety, neglecting the evaluation of models' internal knowledge, particularly physical commonsense. To address this issue, we introduce PhyBench, a comprehensive T2I evaluation dataset comprising 700 prompts across 4 primary categories: mechanics, optics, thermodynamics, and material properties, encompassing 31 distinct physical scenarios. We assess 6 prominent T2I models, including proprietary models DALLE3 and Gemini, and demonstrate that incorporating physical principles into prompts enhances the models' ability to generate physically accurate images. Our findings reveal that: (1) even advanced models frequently err in various physical scenarios, except for optics; (2) GPT-4o, with item-specific scoring instructions, effectively evaluates the models' understanding of physical commonsense, closely aligning with human assessments; and (3) current T2I models are primarily focused on text-to-image translation, lacking profound reasoning regarding physical commonsense. We advocate for increased attention to the inherent knowledge within T2I models, beyond their utility as mere image generation tools. The code and data are available at this https URL . | Computer Vision and Pattern Recognition (cs.CV) | Some low-quality data and comments may mislead readers to understand the paper. We are working hard to correct these problems and resubmit the paper after making the necessary revisions | factual/methodological/other critical errors in manuscript | 14,175 |
2406.12921v2 | WindowMixer: Intra-Window and Inter-Window Modeling for Time Series Forecasting | Time series forecasting (TSF) is crucial in fields like economic forecasting, weather prediction, traffic flow analysis, and public health surveillance. Real-world time series data often include noise, outliers, and missing values, making accurate forecasting challenging. Traditional methods model point-to-point relationships, which limits their ability to capture complex temporal patterns and increases their susceptibility to this http URL address these issues, we introduce the WindowMixer model, built on an all-MLP framework. WindowMixer leverages the continuous nature of time series by examining temporal variations from a window-based perspective. It decomposes time series into trend and seasonal components, handling them individually. For trends, a fully connected (FC) layer makes predictions. For seasonal components, time windows are projected to produce window tokens, processed by Intra-Window-Mixer and Inter-Window-Mixer modules. The Intra-Window-Mixer models relationships within each window, while the Inter-Window-Mixer models relationships between windows. This approach captures intricate patterns and long-range dependencies in the this http URL show WindowMixer consistently outperforms existing methods in both long-term and short-term forecasting tasks. | Machine Learning (cs.LG) | We have found some errors in the paper, involving inaccurate data, and therefore request to withdraw the manuscript | factual/methodological/other critical errors in manuscript | 14,177 |
2406.12924v2 | The Noiseless Quantum Computer Does Not Exist | In this note we show that any logic gates in a quantum computer is informationally dependent on another quantum logic gate. | Quantum Physics (quant-ph) | a wrong formula | factual/methodological/other critical errors in manuscript | 14,178 |
2406.13558v2 | Enhancing Travel Choice Modeling with Large Language Models: A Prompt-Learning Approach | Travel choice analysis is crucial for understanding individual travel behavior to develop appropriate transport policies and recommendation systems in Intelligent Transportation Systems (ITS). Despite extensive research, this domain faces two critical challenges: a) modeling with limited survey data, and b) simultaneously achieving high model explainability and accuracy. In this paper, we introduce a novel prompt-learning-based Large Language Model(LLM) framework that significantly improves prediction accuracy and provides explicit explanations for individual predictions. This framework involves three main steps: transforming input variables into textual form; building of demonstrations similar to the object, and applying these to a well-trained LLM. We tested the framework's efficacy using two widely used choice datasets: London Passenger Mode Choice (LPMC) and Optima-Mode collected in Switzerland. The results indicate that the LLM significantly outperforms state-of-the-art deep learning methods and discrete choice models in predicting people's choices. Additionally, we present a case of explanation illustrating how the LLM framework generates understandable and explicit explanations at the individual level. | Artificial Intelligence (cs.AI) | We currently do not have a replacement version available. We request withdrawal due to a significant methodological error affecting the paper's validity, specifically a miscalculation in data preprocessing. We are working on corrections, but this will take time. We believe an interim withdrawal is necessary to prevent the dissemination of incorrect information. | factual/methodological/other critical errors in manuscript | 14,180 |
2406.15368v2 | Dynamics of Cyclic Contractions | Cyclic contractions generalize the usual contractivities in metric spaces and $b$-MSs. In this paper, we enhance several fixed point theorems related to cyclic (i) Banach self-maps, (ii) Chatterjea contractivities, (iii) Kannan self-mappings, (iv) Ćirić and Hardy-Rogers, and (v) Reich contractions including local versions in $b$-metric spaces while also delineating the associated dynamics. Especially noteworthy is the expansion of the results concerning both fixed and periodic points, which are substantiated across a wider spectrum of ratio values for the aforementioned cyclic contractions within this class of spaces. Additionally, the convergence of Picard iterations towards the fixed point is rigorously established. | Dynamical Systems (math.DS) | Error was found in the paper | factual/methodological/other critical errors in manuscript | 14,182 |
2406.15649v2 | Efficient Human Pose Estimation: Leveraging Advanced Techniques with MediaPipe | This study presents significant enhancements in human pose estimation using the MediaPipe framework. The research focuses on improving accuracy, computational efficiency, and real-time processing capabilities by comprehensively optimising the underlying algorithms. Novel modifications are introduced that substantially enhance pose estimation accuracy across challenging scenarios, such as dynamic movements and partial occlusions. The improved framework is benchmarked against traditional models, demonstrating considerable precision and computational speed gains. The advancements have wide-ranging applications in augmented reality, sports analytics, and healthcare, enabling more immersive experiences, refined performance analysis, and advanced patient monitoring. The study also explores the integration of these enhancements within mobile and embedded systems, addressing the need for computational efficiency and broader accessibility. The implications of this research set a new benchmark for real-time human pose estimation technologies and pave the way for future innovations in the field. The implementation code for the paper is available at this https URL . | Computer Vision and Pattern Recognition (cs.CV) | There is an error in this work. BY mistake in Section 3.3, the angle is calculated wrongly | factual/methodological/other critical errors in manuscript | 14,183 |
2406.16383v2 | Context-augmented Retrieval: A Novel Framework for Fast Information Retrieval based Response Generation using Large Language Model | Generating high-quality answers consistently by providing contextual information embedded in the prompt passed to the Large Language Model (LLM) is dependent on the quality of information retrieval. As the corpus of contextual information grows, the answer/inference quality of Retrieval Augmented Generation (RAG) based Question Answering (QA) systems declines. This work solves this problem by combining classical text classification with the Large Language Model (LLM) to enable quick information retrieval from the vector store and ensure the relevancy of retrieved information. For the same, this work proposes a new approach Context Augmented retrieval (CAR), where partitioning of vector database by real-time classification of information flowing into the corpus is done. CAR demonstrates good quality answer generation along with significant reduction in information retrieval and answer generation time. | Information Retrieval (cs.IR) | Because the dataset in which the model was trained upon wasn't consistent across different sections so it was preferred to delete this preprint | factual/methodological/other critical errors in manuscript | 14,184 |
2406.16385v2 | Validity condition for high-fidelity Digitized Quantum Annealing | Digitizing an adiabatic evolution is a strategy able to combine the good performance of gate-based quantum processors with the advantages of adiabatic algorithms, providing then a hybrid model for efficient quantum information processing. In this work we develop validity conditions for high fidelity digital adiabatic tasks. To this end, we assume a digitizing process based on the Suzuki-Trotter decomposition, which allows us to introduce a $Digitized$ $Adiabatic$ $Theorem$. As consequence of this theorem, we show that the performance of such a hybrid model is limited by the fundamental constraints on the adiabatic theorem validity, even in ideal quantum processors. We argue how our approach predicts the existence of intrinsic non-adiabatic errors reported by R. Barends $et$ $al$., Nature 534, 222 (2016) through an empirical study of digital annealing. In addition, our approach allows us to explain the existence of a scaling of the number of Suzuki-Trotter blocks for the optimal digital circuit with respect to the optimal adiabatic total evolution time, as reported by G. B. Mbeng $et$ $al$, Phys. Rev. B 100, 224201 (2019) through robust numerical analysis of digital annealing. We illustrate our results through two examples of digitized adiabatic algorithms, namely, the two-qubits exact-cover problem and the three-qubits adiabatic factorization of the number 21. | Quantum Physics (quant-ph) | In this version of the paper we can see mistakes and demonstration errors (mainly in abstract). In addition, it is in conflict interest with other authors | factual/methodological/other critical errors in manuscript | 14,185 |
2407.00554v2 | Variational approach to nonlinear pulse evolution in stock derivative markets | The Ivancevic option pricing model is studied via variational approach. Both the Gaussian anstz and the (sech ansatz are used, and each has a unique results from one another. But in terms of existance of soliton solutions they both agree that hot market temperatures support the existance of soliton solutions. | Pattern Formation and Solitons (nlin.PS) | I want it removed since it is theoretically incorrect. I derived the dispersion relation in terms of the chirp Eq.10 and Eq.18 describing them to influence the shape of the soliton depending on whether the dispersion is real or imaginary | factual/methodological/other critical errors in manuscript | 14,190 |
2407.01829v2 | Notes on Siegfried Bosch's Algebraic Geometry and Commutative Algebra (dedicated to Grothendieck) | Notes on Commutative Alegbra and Algebraic Geometry covering rings, ideals, modules, presheaves, sheaves, schemes, homological algebra, étale cohomology and further topics that are more advanced. | Algebraic Geometry (math.AG) | Mathematical inaccuracies in the paper | factual/methodological/other critical errors in manuscript | 14,192 |
2407.02110v2 | On the uniqueness of the strictly convex quadrilateral central configuration with a fixed angle | The conjecture of the existence and the uniqueness of the strictly convex quadrilateral central configuration for the Newtonian 4-body problem is one of the most-talked open problems in the study of the classical n-body problems in celestial mechanics. MacMillan and Bartky first gave its general existence in the 1930s and a particular case for its uniqueness. Still, the general case has yet to be solved perfectly since it was considered by Sim'{o} and Yoccoz in the 1980s and was first mentioned by Albouy and Fu in 2008 in the formal publication. Using coordinates of mutual distances and Morse's critical point theory, we give the (at most) uniqueness of the planar strictly convex 4-body central configuration when the angle of one pair of the opposite sides is given. | Mathematical Physics (math-ph) | Proposition 2 and Lemma 1 are incorrect, which are essential to the structure and the main result of this paper. So, we need some time to withdraw it first and then try to revise the manuscript. Thank you! | factual/methodological/other critical errors in manuscript | 14,194 |
2407.02517v2 | CAV-AHDV-CAV: Mitigating Traffic Oscillations for CAVs through a Novel Car-Following Structure and Reinforcement Learning | Connected and Automated Vehicles (CAVs) offer a promising solution to the challenges of mixed traffic with both CAVs and Human-Driven Vehicles (HDVs). A significant hurdle in such scenarios is traffic oscillation, or the "stop-and-go" pattern, during car-following situations. While HDVs rely on limited information, CAVs can leverage data from other CAVs for better decision-making. This allows CAVs to anticipate and mitigate the spread of deceleration waves that worsen traffic flow. We propose a novel "CAV-AHDV-CAV" car-following framework that treats the sequence of HDVs between two CAVs as a single entity, eliminating noise from individual driver behaviors. This deep reinforcement learning approach analyzes vehicle equilibrium states and employs a state fusion strategy. Trained and tested on diverse datasets (HighD, NGSIM, SPMD, Waymo, Lyft) encompassing over 70,000 car-following instances, our model outperforms baselines in collision avoidance, maintaining equilibrium with both preceding and leading vehicles and achieving the lowest standard deviation of time headway. These results demonstrate the effectiveness of our approach in developing robust CAV control strategies for mixed traffic. Our model has the potential to mitigate traffic oscillation, improve traffic flow efficiency, and enhance overall safety. | Robotics (cs.RO) | Due to errors identified in the experimental methodology and results sections, we request to withdraw this paper | factual/methodological/other critical errors in manuscript | 14,195 |
2407.04410v3 | On the Existence of an Extremal Function for the Delsarte Extremal Problem | In the general setting of a locally compact Abelian group $G$, the Delsarte extremal problem asks for the supremum of integrals over the collection of continuous positive definite functions $f: G \to \mathbb{R}$ satisfying $f(0) = 1$ and having $\mathrm{supp} f_{+} \subset \Omega$ for some measurable subset $\Omega$ of finite measure. In this paper, we consider the question of the existence of an extremal function for the Delsarte extremal problem. In particular, we show that there exists an extremal function for the Delsarte problem when $\Omega$ is closed, extending previously known existence results to a larger class of functions. | Classical Analysis and ODEs (math.CA) | Error in line 10 of Theorem 7. The subsequence only converges uniformly on compact subsets if the limit function f satisfies f(0)=1 and it continuous, which we do not a priori know | factual/methodological/other critical errors in manuscript | 14,196 |
2407.06913v2 | A Simple, Nearly-Optimal Algorithm for Differentially Private All-Pairs Shortest Distances | The all-pairs shortest distances (APSD) with differential privacy (DP) problem takes as input an undirected, weighted graph $G = (V,E, \mathbf{w})$ and outputs a private estimate of the shortest distances in $G$ between all pairs of vertices. In this paper, we present a simple $\widetilde{O}(n^{1/3}/\varepsilon)$-accurate algorithm to solve APSD with $\varepsilon$-DP, which reduces to $\widetilde{O}(n^{1/4}/\varepsilon)$ in the $(\varepsilon, \delta)$-DP setting, where $n = |V|$. Our algorithm greatly improves upon the error of prior algorithms, namely $\widetilde{O}(n^{2/3}/\varepsilon)$ and $\widetilde{O}(\sqrt{n}/\varepsilon)$ in the two respective settings, and is the first to be optimal up to a polylogarithmic factor, based on a lower bound of $\widetilde{\Omega}(n^{1/4})$. In the case where a multiplicative approximation is allowed, we give two different constructions of algorithms with reduced additive error. Our first construction allows a multiplicative approximation of $O(k\log{\log{n}})$ and has additive error $\widetilde{O}(k\cdot n^{1/k}/\varepsilon)$ in the $\varepsilon$-DP case and $\widetilde{O}(\sqrt{k}\cdot n^{1/(2k)}/\varepsilon)$ in the $(\varepsilon, \delta)$-DP case. Our second construction allows multiplicative approximation $2k-1$ and has the same asymptotic additive error as the first construction. Both constructions significantly improve upon the currently best-known additive error of, $\widetilde{O}(k\cdot n^{1/2 + 1/(4k+2)}/\varepsilon)$ and $\widetilde{O}(k\cdot n^{1/3 + 2/(9k+3)}/\varepsilon)$, respectively. Our algorithms are straightforward and work by decomposing a graph into a set of spanning trees, and applying a key observation that we can privately release APSD in trees with $O(\text{polylog}(n))$ error. | Data Structures and Algorithms (cs.DS) | Error in Section 3: (1) Improper assumption that the topology of the shortest path trees are public. (2) Improper usage of Lemma 2.4. Error in Section 4: Improper assumption that the topology of the shortest path trees are public | factual/methodological/other critical errors in manuscript | 14,198 |
2407.08401v2 | Data-Driven Model Predictive Control for Autonomous Vehicle Steering | With the development of autonomous driving technology, there are increasing demands for vehicle control, and MPC has become a widely researched topic in both industry and academia. Existing MPC control methods based on vehicle kinematics or dynamics have challenges such as difficult modeling, numerous parameters, strong nonlinearity, and high computational cost. To address these issues, this paper proposes a Data-Driven MPC control method for autonomous vehicle steering. This method avoids the need for complex vehicle system modeling and achieves trajectory tracking with relatively low computational time and small errors. We validate the control effectiveness of our algorithm in specific scenario through CarSim-Simulink simulation and perform comparative analysis with PID and vehicle kinematics MPC, confirming the feasibility and superiority of the proposed algorithm. | Systems and Control (eess.SY) | Some parts of the article need to be revised, and the methodology may not be applicable to the issue at hand | factual/methodological/other critical errors in manuscript | 14,204 |
2407.09178v2 | Shafarevich-Tate groups of holomorphic Lagrangian fibrations II | Let $X$ be a compact hyperkähler manifold with a Lagrangian fibration $\pi\colon X\to B$. A Shafarevich-Tate twist of $X$ is a holomorphic symplectic manifold with a Lagrangian fibration $\pi^\varphi\colon X^\varphi\to B$ which is isomorphic to $\pi$ locally over the base. In particular, $\pi^\varphi$ has the same fibers as $\pi$. A twist $X^\varphi$ corresponds to an element $\varphi$ in the Shafarevich-Tate group of $X$. We show that $X^\varphi$ is Kähler when a multiple of $\varphi$ lies in the connected component of unity of the Shafarevich-Tate group and give a necessary condition for $X^\varphi$ to be bimeromorphic to a Kähler manifold. | Algebraic Geometry (math.AG) | Working on fixing a mistake in the section on Kähler twists | factual/methodological/other critical errors in manuscript | 14,207 |
2407.11652v3 | CCVA-FL: Cross-Client Variations Adaptive Federated Learning for Medical Imaging | Federated Learning (FL) offers a privacy-preserving approach to train models on decentralized data. Its potential in healthcare is significant, but challenges arise due to cross-client variations in medical image data, exacerbated by limited annotations. This paper introduces Cross-Client Variations Adaptive Federated Learning (CCVA-FL) to address these issues. CCVA-FL aims to minimize cross-client variations by transforming images into a common feature space. It involves expert annotation of a subset of images from each client, followed by the selection of a client with the least data complexity as the target. Synthetic medical images are then generated using Scalable Diffusion Models with Transformers (DiT) based on the target client's annotated images. These synthetic images, capturing diversity and representing the original data, are shared with other clients. Each client then translates its local images into the target image space using image-to-image translation. The translated images are subsequently used in a federated learning setting to develop a server model. Our results demonstrate that CCVA-FL outperforms Vanilla Federated Averaging by effectively addressing data distribution differences across clients without compromising privacy. | Computer Vision and Pattern Recognition (cs.CV) | I found critical errors in the manuscript affecting its validity. I need to correct these before resubmitting. Major changes to methodology and results are underway, significantly altering the content. I will resubmit the revised version | factual/methodological/other critical errors in manuscript | 14,209 |
2407.12022v2 | ITERTL: An Iterative Framework for Fine-tuning LLMs for RTL Code Generation | Recently, large language models (LLMs) have demonstrated excellent performance in understanding human instructions and generating code, which has inspired researchers to explore the feasibility of generating RTL code with LLMs. However, the existing approaches to fine-tune LLMs on RTL codes typically are conducted on fixed datasets, which do not fully stimulate the capability of LLMs and require large amounts of reference data. To mitigate these issues , we introduce a simple yet effective iterative training paradigm named ITERTL. During each iteration, samples are drawn from the model trained in the previous cycle. Then these new samples are employed for training in this loop. Through this iterative approach, the distribution mismatch between the model and the training samples is reduced. Additionally, the model is thus enabled to explore a broader generative space and receive more comprehensive feedback. Theoretical analyses are conducted to investigate the mechanism of the effectiveness. Experimental results show the model trained through our proposed approach can compete with and even outperform the state-of-the-art (SOTA) open-source model with nearly 37\% reference samples, achieving remarkable 42.9\% and 62.2\% pass@1 rate on two VerilogEval evaluation datasets respectively. While using the same amount of reference samples, our method can achieved a relative improvement of 16.9\% and 12.5\% in pass@1 compared to the non-iterative method. This study facilitates the application of LLMs for generating RTL code in practical scenarios with limited data. | Computation and Language (cs.CL) | There is some mistakes about the [REDACTED-NAME] in Section4.1 | factual/methodological/other critical errors in manuscript | 14,211 |
2407.13070v2 | The Cost of Arbitrariness for Individuals: Examining the Legal and Technical Challenges of Model Multiplicity | Model multiplicity, the phenomenon where multiple models achieve similar performance despite different underlying learned functions, introduces arbitrariness in model selection. While this arbitrariness may seem inconsequential in expectation, its impact on individuals can be severe. This paper explores various individual concerns stemming from multiplicity, including the effects of arbitrariness beyond final predictions, disparate arbitrariness for individuals belonging to protected groups, and the challenges associated with the arbitrariness of a single algorithmic system creating a monopoly across various contexts. It provides both an empirical examination of these concerns and a comprehensive analysis from the legal standpoint, addressing how these issues are perceived in the anti-discrimination law in Canada. We conclude the discussion with technical challenges in the current landscape of model multiplicity to meet legal requirements and the legal gap between current law and the implications of arbitrariness in model selection, highlighting relevant future research directions for both disciplines. | Computers and Society (cs.CY) | Current version of the paper contains errors in the attribution of previous work. We are working on creating a new version, which can take a while and thus are withdrawing this version in the meantime | factual/methodological/other critical errors in manuscript | 14,212 |
2407.16146v2 | On the existence of relative injective envelopes on ring extensions | Let $f:S\rightarrow R$ be a ring extension. Then every $R$-module has an $(R,S)$-injective envelope, positively answering an open question provided by Guo [9]. | Rings and Algebras (math.RA) | There is an error in the proof of the main result | factual/methodological/other critical errors in manuscript | 14,213 |
2407.17036v2 | A Bayesian modelling framework for health care resource use and costs in trial-based economic evaluations | Individual-level effectiveness and healthcare resource use (HRU) data are routinely collected in trial-based economic evaluations. While effectiveness is often expressed in terms of utility scores derived from some health-related quality of life instruments (e.g.~EQ-5D questionnaires), different types of HRU may be included. Costs are usually generated by applying unit prices to HRU data and statistical methods have been traditionally implemented to analyse costs and utilities or after combining them into aggregated variables (e.g. Quality-Adjusted Life Years). When outcome data are not fully observed, e.g. some patients drop out or only provided partial information, the validity of the results may be hindered both in terms of efficiency and bias. Often, partially-complete HRU data are handled using "ad-hoc" methods, implicitly relying on some assumptions (e.g. fill-in a zero) which are hard to justify beside the practical convenience of increasing the completion rate. We present a general Bayesian framework for the modelling of partially-observed HRUs which allows a flexible model specification to accommodate the typical complexities of the data and to quantify the impact of different types of uncertainty on the results. We show the benefits of using our approach using a motivating example and compare the results to those from traditional analyses focussed on the modelling of cost variables after adopting some ad-hoc imputation strategy for HRU data. | Methodology (stat.ME) | Error: estimates reported in Table 3 are incorrect and need to be doubled checked before being published due to issue in coding of the model discovered. Same for all results displayed based on the models | factual/methodological/other critical errors in manuscript | 14,219 |
2407.18406v2 | A form of refined Roth's theorem and its application to the $abc$-conjecture | In this paper, we give a form of refined Roth's theorem. As an application, we prove a special case of the $abc$-conjecture. | Number Theory (math.NT) | There is an error in Theorem 1.6 | factual/methodological/other critical errors in manuscript | 14,221 |
2407.19061v3 | A Relationship Between Nonphysical Quasi-probabilities and Nonlocality Objectivity | Density matrices are the most general descriptions of quantum states, covering both pure and mixed states. Positive semidefiniteness is a physical requirement of density matrices, imposing nonnegative probabilities of measuring physical values. Separately, nonlocality is a property shared by some bipartite quantum systems, indicating a correlation of the component parts that cannot be described by local classical variables. In this work, we show that breaking the positive-semidefinite requirement and allowing states with a negative minimal eigenvalue arbitrarily close to zero, allows for the construction of states that are nonlocal under one component labelling but local when the labelling is interchanged. This is an observer-dependent nonlocality, showing the connection between nonlocal objectivism and negative quasi-probabilities. | Quantum Physics (quant-ph) | An error in the calculation of the eigenvalues for β^{T}βfor the right-identity case (Sec. 3, eq. 8 line 1). In fact the eigenvalues are the same for both left- and right- identities, leaving the main result null and void | factual/methodological/other critical errors in manuscript | 14,222 |
2407.19323v3 | MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo | Reconstructing textureless areas in MVS poses challenges due to the absence of reliable pixel correspondences within fixed patch. Although certain methods employ patch deformation to expand the receptive field, their patches mistakenly skip depth edges to calculate areas with depth discontinuity, thereby causing ambiguity. Consequently, we introduce Multi-granularity Segmentation Prior Multi-View Stereo (MSP-MVS). Specifically, we first propose multi-granularity segmentation prior by integrating multi-granularity depth edges to restrict patch deformation within homogeneous areas. Moreover, we present anchor equidistribution that bring deformed patches with more uniformly distributed anchors to ensure an adequate coverage of their own homogeneous areas. Furthermore, we introduce iterative local search optimization to represent larger patch with sparse representative candidates, significantly boosting the expressive capacity for each patch. The state-of-the-art results on ETH3D and Tanks & Temples benchmarks demonstrate the effectiveness and robust generalization ability of our proposed method. | Computer Vision and Pattern Recognition (cs.CV) | After a thorough internal review, we identified a significant error in the experimental design described in the Multi-granularity [REDACTED-NAME] Section of our paper, which impacts the accuracy of the data analysis and conclusions. We are in the process of correcting these errors and will submit an updated version in due course | factual/methodological/other critical errors in manuscript | 14,224 |
2407.20191v3 | Three-dimensional inverse acoustic scattering problem by the BC-method | The forward acoustic scattering problem is to find $u=u^f(x,t)$ satisfying \begin{align*} &u_{tt}-\Delta u+qu=0, && (x,t) \in {\mathbb R}^3 \times (-\infty,\infty); \\ &u \mid_{|x|<-t} =0 , && t<0;\\ &\lim_{s \to -\infty} s\,u((-s+\tau)\,\omega,s)=f(\tau,\omega), && (\tau,\omega) \in \Sigma:=[0,\infty)\times S^2; \end{align*} for a real valued compactly supported potential $q=q(x)$ and a control $f \in L_2(\Sigma)$. The map $R: L_2(\Sigma)\to L_2(\Sigma)$, \begin{align*} & (Rf)(\tau ,\omega )\,:= \lim_{s \to +\infty} s\, u^f((s+\tau )\,\omega ,s), \quad (\tau ,\omega ) \in \Sigma \end{align*} is a response operator. The inverse problem is to determine $q$ from $R$. It is solved by a relevant version of the boundary control method. The procedure that recovers the potential is local: for any fixed $\xi>0$, given $R\upharpoonright\{f\in L_2(\Sigma)\,|\,\,f\mid_{0\leqslant \tau<\xi}=0\}$ it determines $q\big|_{|x|\geqslant\xi}$. | Analysis of PDEs (math.AP) | A few mistakes and inaccuracies are found out. F new version is in preparation | factual/methodological/other critical errors in manuscript | 14,225 |
2407.20651v2 | Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations | General intelligence requires quick adaption across tasks. While existing reinforcement learning (RL) methods have made progress in generalization, they typically assume only distribution changes between source and target domains. In this paper, we explore a wider range of scenarios where both the distribution and environment spaces may change. For example, in Atari games, we train agents to generalize to tasks with different levels of mode and difficulty, where there could be new state or action variables that never occurred in previous environments. To address this challenging setting, we introduce a causality-guided self-adaptive representation-based approach, called CSR, that equips the agent to generalize effectively and efficiently across a sequence of tasks with evolving dynamics. Specifically, we employ causal representation learning to characterize the latent causal variables and world models within the RL system. Such compact causal representations uncover the structural relationships among variables, enabling the agent to autonomously determine whether changes in the environment stem from distribution shifts or variations in space, and to precisely locate these changes. We then devise a three-step strategy to fine-tune the model under different scenarios accordingly. Empirical experiments show that CSR efficiently adapts to the target domains with only a few samples and outperforms state-of-the-art baselines on a wide range of scenarios, including our simulated environments, Cartpole, and Atari games. | Machine Learning (cs.LG) | This paper was submitted to NeurIPS24. According to the reviews, there are some mistakes in the Theorems in this papers. Moreover, we will choose some other environments for experiments, which means that it takes at least months to update/rewrite the Experiment & [REDACTED-NAME]. So we need to withdraw this paper for major revision | factual/methodological/other critical errors in manuscript | 14,226 |
2408.00226v2 | Shadow of a Renormalization Group Improved Regular Rotating Black Hole | We present a study on quantum gravity effects on the shadow of a regular rotating black hole (BH) obtained in the setting of the asymptotic safety (AS) gravity. We show that the rotating metric, which results from a static regular one recently presented in the literature, remains regular after being constructed using the generalized Newman-Janis (NJ) algorithm.. The novelty of the static regular metric lies in the fact that it is the outcome of an effective Lagrangian which describes dust whose spherically symmetric collapse is non-singular as a consequence of the antiscreening character of gravity at small distances. The effective Lagrangian includes a multiplicative coupling, denoted as chi, with the Lagrangian of the collapsing fluid. The resulting exterior metric for large radii depends on a free parameter xi which captures the quantum gravity effects. The form of the coupling chi and its connection with the quantum parameter xi are determined by the running of the Newton coupling G(k) along a renormalization group trajectory that stops at the ultraviolet (UV) non-gaussian fixed point of the AS theory. Varying both the spin parameter a/M and the quantum parameter xi, we explore the quantum gravity effects on several astronomical observables used to describe the shadow features of rotating BHs. In order to obtain constraints on the parameter xi, we confront our results with the recent EHT observations of the shadows of the supermassive BHs M87 and Sgr A. We find that the ranges of variation of all the studied shadow observables fall entirely within the ranges determined by the EHT collaboration. We then conclude that the current astronomical data do not rule out the renormalization group improved regular rotating BH. | General Relativity and Quantum Cosmology (gr-qc) | This paper has been withdrawn due to an algebraic error which led to the wrong conclusion that the rotating BH is regular | factual/methodological/other critical errors in manuscript | 14,229 |
2408.03258v2 | On branch and cut approach for q-Allocation Hub Interdiction Problem | Many industries widely adopted hub networks these days. Managing logistics, transportation, and distribution requires a delicate balance to ensure seamless operations within this network. Hub network promotes cost-effective routing through inter-hub flows. Failure of such hubs may impact the total network with huge costs. In this paper, we study bilevel $q$-allocation hub interdiction problem. In previous literature hub interdiction problem was studied with single and multiple allocation this http URL problem focus on $q$ allocation which solves single and multiple allocation problem as special case. We also show improvements on the branch and cut approach by using cutting this http URL experiments based on large instances present the efficiency of the approach to solve some previously unsolved instances. | Optimization and Control (math.OC) | There are some technical errors in the paper. The pareto section is not right and computational results are missing | factual/methodological/other critical errors in manuscript | 14,231 |
2408.04316v2 | Explicit expression and fast algorithms for the inverse of some matrices arising from implicit time integration | In this paper, we first present an explicit expression for the inverse\emph{} of a type of matrices. As special applications, the inverse of some matrices arising from implicit time integration techniques, such as the well-known implicit Runge-Kutta schemes and block implicit methods, can also be explicitly determined. Adiitionally, we introduce three fast algorithms for computing the elements of the inverse of these matrices in $O(n^2)$ arithmetic operations, i.e., the first one is based on Traub algorithm for fast inversion of Vandermonde matrices, while the other two utilize the special structure of the matrices. Finally, some symbolic and numerical results are presented to show that our algorithms are both highly efficient and accurate. | Numerical Analysis (math.NA) | There is error in the proof of Theorem 2.2 in Section 2, So the formula (2.10) is wrong. And the numerical results in section 4 may be not correct due to the wrong formula. In order to not misleading the reader, we hope to withdraw this paper, many thanks | factual/methodological/other critical errors in manuscript | 14,233 |
2408.04957v3 | LLaVA-VSD: Large Language-and-Vision Assistant for Visual Spatial Description | Visual Spatial Description (VSD) aims to generate texts that describe the spatial relationships between objects within images. Traditional visual spatial relationship classification (VSRC) methods typically output the spatial relationship between two objects in an image, often neglecting world knowledge and lacking general language capabilities. In this paper, we propose a Large Language-and-Vision Assistant for Visual Spatial Description, named LLaVA-VSD, which is designed for the classification, description, and open-ended description of visual spatial relationships. Specifically, the model first constructs a VSD instruction-following dataset using given figure-caption pairs for the three tasks. It then employs LoRA to fine-tune a Large Language and Vision Assistant for VSD, which has 13 billion parameters and supports high-resolution images. Finally, a large language model (Qwen-2) is used to refine the generated sentences, enhancing their diversity and accuracy. LLaVA-VSD demonstrates excellent multimodal conversational capabilities and can follow open-ended instructions to assist with inquiries about object relationships in images. | Computer Vision and Pattern Recognition (cs.CV) | We have discovered a significant error in the paper that affects the main conclusions. To ensure the accuracy of our research, we have decided to withdraw this paper and will resubmit it after making the necessary corrections | factual/methodological/other critical errors in manuscript | 14,234 |
2408.08124v4 | Sub-terahertz field emission transistors with selfpackaged microcavities | This paper presents the design of a vertical structure terahertz field emission transistor that utilizes a high-angle oblique deposition method to form a self-packaged vacuum microcavity. The simulation demonstrates that the self-packaged microcavity can effectively mitigate the potential impact of conventional field emission transistors on surrounding solid-state circuits, thereby improving the frequency performance and stability of the device. The proposed design exhibits a cutoff frequency at the sub-terahertz level. | Plasma Physics (physics.plasm-ph) | Achieving reliable simulation of closed new domain formation processes using a single phase-field method is unconvincing and requires the use of multiple algorithms for parallel comparison with experiments | factual/methodological/other critical errors in manuscript | 14,235 |
2408.08780v3 | Large Language Models Might Not Care What You Are Saying: Prompt Format Beats Descriptions | With the help of in-context learning (ICL), large language models (LLMs) have achieved impressive performance across various tasks. However, the function of descriptive instructions during ICL remains under-explored. In this work, we propose an ensemble prompt framework to describe the selection criteria of multiple in-context examples, and preliminary experiments on machine translation (MT) across six translation directions confirm that this framework boosts ICL perfromance. But to our surprise, LLMs might not necessarily care what the descriptions actually say, and the performance gain is primarily caused by the ensemble format, since the framework could lead to improvement even with random descriptive nouns. We further apply this new ensemble prompt on a range of commonsense, math, logical reasoning and hallucination tasks with three LLMs and achieve promising results, suggesting again that designing a proper prompt format would be much more effective and efficient than paying effort into specific descriptions. Our code will be publicly available once this paper is published. | Computation and Language (cs.CL) | There are some mistakes in the experimental data | factual/methodological/other critical errors in manuscript | 14,236 |
2408.09172v3 | Unc-TTP: A Method for Classifying LLM Uncertainty to Improve In-Context Example Selection | Nowadays, Large Language Models (LLMs) have demonstrated exceptional performance across various downstream tasks. However, it is challenging for users to discern whether the responses are generated with certainty or are fabricated to meet user expectations. Estimating the uncertainty of LLMs is particularly challenging due to their vast scale and the lack of white-box access. In this work, we propose a novel Uncertainty Tripartite Testing Paradigm (Unc-TTP) to classify LLM uncertainty, via evaluating the consistency of LLM outputs when incorporating label interference into the sampling-based approach. Based on Unc-TTP outputs, we aggregate instances into certain and uncertain categories. Further, we conduct a detailed analysis of the uncertainty properties of LLMs and show Unc-TTP's superiority over the existing sampling-based methods. In addition, we leverage the obtained uncertainty information to guide in-context example selection, demonstrating that Unc-TTP obviously outperforms retrieval-based and sampling-based approaches in selecting more informative examples. Our work paves a new way to classify the uncertainty of both open- and closed-source LLMs, and introduces a practical approach to exploit this uncertainty to improve LLMs performance. | Artificial Intelligence (cs.AI) | The model diagram in Figure 1 on page 3 of the paper has significant ambiguities. It may lead readers to mistakenly believe that the experiments were conducted in a multi-turn dialogue format. Therefore, we request the withdrawal of this submission | factual/methodological/other critical errors in manuscript | 14,237 |
2408.12067v2 | Distributed Noncoherent Joint Transmission Based on Multi-Agent Reinforcement Learning for Dense Small Cell MISO Systems | We consider a dense small cell (DSC) network where multi-antenna small cell base stations (SBSs) transmit data to single-antenna users over a shared frequency band. To enhance capacity, a state-of-the-art technique known as noncoherent joint transmission (JT) is applied, enabling users to receive data from multiple coordinated SBSs. However, the sum rate maximization problem with noncoherent JT is inherently nonconvex and NP-hard. While existing optimization-based noncoherent JT algorithms can provide near-optimal performance, they require global channel state information (CSI) and multiple iterations, which makes them difficult to be implemeted in DSC this http URL overcome these challenges, we first prove that the optimal beamforming structure is the same for both the power minimization problem and the sum rate maximization problem, and then mathematically derive the optimal beamforming structure for both problems by solving the power minimization this http URL optimal beamforming structure can effectively reduces the variable this http URL exploiting the optimal beamforming structure, we propose a deep deterministic policy gradient-based distributed noncoherent JT scheme to maximize the system sum this http URL the proposed scheme, each SBS utilizes global information for training and uses local CSI to determine beamforming vectors. Simulation results demonstrate that the proposed scheme achieves comparable performance with considerably lower computational complexity and information overhead compared to centralized iterative optimization-based techniques, making it more attractive for practical deployment. | Signal Processing (eess.SP) | After thorough discussions with my co-authors, we have identified certain issues with the paper that cannot be resolved through revisions. As a result, we have collectively decided to complete withdraw the paper from arXiv | factual/methodological/other critical errors in manuscript | 14,242 |
2408.13589v2 | $s$-Modular, $s$-congruent and $s$-duplicate partitions | In this paper, we investigate the combinatorial properties of three classes of integer partitions: (1) $s$-modular partitions, a class consisting of partitions into parts with a number of occurrences (i.e., multiplicity) congruent to $0$ or $1$ modulo $s$, (2) $s$-congruent partitions, which generalize Sellers' partitions into parts not congruent to $2$ modulo $4$, and (3) $s$-duplicate partitions, of which the partitions having distinct odd parts and enumerated by the function $\mypod(n)$ are a special case. In this vein, we generalize Alladi's series expansion for the product generating function of $\mypod(n)$ and show that Andrews' generalization of Göllnitz-Gordon identities coincides with the number of partitions into parts simultaneously $s$-congruent and $t$-distinct (parts appearing fewer than $t$ times). | Combinatorics (math.CO) | There are somme mathematical errors in the paper, we will correct after we will put it in arXiv | factual/methodological/other critical errors in manuscript | 14,243 |
2408.16134v2 | A transition state resonance radically reshapes angular distributions of the F + H2 -> F H(vf = 3) + H reaction in the 62.09-101.67 meV energy range | Reactive angular distributions of the benchmark F + H2(vi = 0) -> F H(vf = 3) + H reaction show unusual propensity towards small scattering angles, a subject of a long debate in the literature. We use Regge trajectories to quantify the resonance contributions to state-to-state differential cross sections. Conversion to complex energy poles allows us to attribute the effect almost exclusively to a transition state resonance, long known to exist in the F +H2 system and its isotopic variant F +HD. For our detailed analysis of angular scattering we employ the package DCS Regge, recently developed for the purpose [Comp. Phys. Comm., 2022, 277, 108370.] | Quantum Physics (quant-ph) | Inaccuracies in the version 1. Will be replaced with version 2, with a slightly changed title | factual/methodological/other critical errors in manuscript | 14,246 |
2408.16162v2 | Every Polish group has a non-trivial topological group automorphism | We prove that every Polish group admits a non-trivial topological group automorphism. This answers a question posed by Forte Shinko. As a consequence, we prove that there are no uniquely homogeneous Polish groups. | Logic (math.LO) | The argument in the last paragraph of the proof of Theorem 1.1 is faulty. Concretely, when we extend a non-trivial automorphism of L to the whole group by fixing any element of a maximal independent subset Y of U, we redefine the automorphism for the elements of L that are generated by Y. We thank [REDACTED-NAME] for pointing out this mistake | factual/methodological/other critical errors in manuscript | 14,247 |
2408.16437v2 | Direct finiteness of representable regular rings with involution: A counterexample | Bruns and Roddy constructed a $3$-generated modular ortholattice $L$ which cannot be embedded into any complete modular ortholattice. Motivated by their approach, we use shift operators to construct a $*$-regular $*$-ring $R$ of endomorphisms of an inner product space (which can be chosen as the Hilbert space $\ell^2$) such that direct finiteness fails for $R$. | Rings and Algebras (math.RA) | As observed by Wehrung, the identity minus shift has no quasi-inverse in the ring of row and column finite matrices. Thus, the claimed example does not work | factual/methodological/other critical errors in manuscript | 14,249 |
2409.00381v2 | 3D Gaussian Splatting for Large-scale 3D Surface Reconstruction from Aerial Images | Recently, 3D Gaussian Splatting (3DGS) has garnered significant attention. However, the unstructured nature of 3DGS poses challenges for large-scale surface reconstruction from aerial images. To address this gap, we propose the first large-scale surface reconstruction method for multi-view stereo (MVS) aerial images based on 3DGS, named Aerial Gaussian Splatting (AGS). Initially, we introduce a data chunking method tailored for large-scale aerial imagery, making the modern 3DGS technology feasible for surface reconstruction over extensive scenes. Additionally, we integrate the Ray-Gaussian Intersection method to obtain normal and depth information, facilitating geometric constraints. Finally, we introduce a multi-view geometric consistency constraint to enhance global geometric consistency and improve reconstruction accuracy. Our experiments on multiple datasets demonstrate for the first time that the GS-based technique can match traditional aerial MVS methods on geometric accuracy, and beat state-of-the-art GS-based methods on geometry and rendering quality. | Computer Vision and Pattern Recognition (cs.CV) | In the writing, some parts of the book were wrong and needed a large revision | factual/methodological/other critical errors in manuscript | 14,251 |
2409.00815v2 | Serialized Speech Information Guidance with Overlapped Encoding Separation for Multi-Speaker Automatic Speech Recognition | Serialized output training (SOT) attracts increasing attention due to its convenience and flexibility for multi-speaker automatic speech recognition (ASR). However, it is not easy to train with attention loss only. In this paper, we propose the overlapped encoding separation (EncSep) to fully utilize the benefits of the connectionist temporal classification (CTC) and attention hybrid loss. This additional separator is inserted after the encoder to extract the multi-speaker information with CTC losses. Furthermore, we propose the serialized speech information guidance SOT (GEncSep) to further utilize the separated encodings. The separated streams are concatenated to provide single-speaker information to guide attention during decoding. The experimental results on LibriMix show that the single-speaker encoding can be separated from the overlapped encoding. The CTC loss helps to improve the encoder representation under complex scenarios. GEncSep further improved performance. | Sound (cs.SD) | something wrong with input data | factual/methodological/other critical errors in manuscript | 14,252 |
2409.01021v2 | CONDA: Condensed Deep Association Learning for Co-Salient Object Detection | Inter-image association modeling is crucial for co-salient object detection. Despite satisfactory performance, previous methods still have limitations on sufficient inter-image association modeling. Because most of them focus on image feature optimization under the guidance of heuristically calculated raw inter-image associations. They directly rely on raw associations which are not reliable in complex scenarios, and their image feature optimization approach is not explicit for inter-image association modeling. To alleviate these limitations, this paper proposes a deep association learning strategy that deploys deep networks on raw associations to explicitly transform them into deep association features. Specifically, we first create hyperassociations to collect dense pixel-pair-wise raw associations and then deploys deep aggregation networks on them. We design a progressive association generation module for this purpose with additional enhancement of the hyperassociation calculation. More importantly, we propose a correspondence-induced association condensation module that introduces a pretext task, i.e. semantic correspondence estimation, to condense the hyperassociations for computational burden reduction and noise elimination. We also design an object-aware cycle consistency loss for high-quality correspondence estimations. Experimental results in three benchmark datasets demonstrate the remarkable effectiveness of our proposed method with various training settings. | Computer Vision and Pattern Recognition (cs.CV) | There is an error. [REDACTED-NAME] 4.1, the number of images in some dataset is incorrect and needs to be revised | factual/methodological/other critical errors in manuscript | 14,254 |
2409.01137v3 | Smart E-commerce Recommendations with Semantic AI | In e-commerce, web mining for page recommendations is widely used but often fails to meet user needs. To address this, we propose a novel solution combining semantic web mining with BP neural networks. We process user search logs to extract five key features: content priority, time spent, user feedback, recommendation semantics, and input deviation. These features are then fed into a BP neural network to classify and prioritize web pages. The prioritized pages are recommended to users. Using book sales pages for testing, our results demonstrate that this solution can quickly and accurately identify the pages users need. Our approach ensures that recommendations are more relevant and tailored to individual preferences, enhancing the online shopping experience. By leveraging advanced semantic analysis and neural network techniques, we bridge the gap between user expectations and actual recommendations. This innovative method not only improves accuracy but also speeds up the recommendation process, making it a valuable tool for e-commerce platforms aiming to boost user satisfaction and engagement. Additionally, our system ability to handle large datasets and provide real-time recommendations makes it a scalable and efficient solution for modern e-commerce challenges. | Information Retrieval (cs.IR) | My paper contain some errors | factual/methodological/other critical errors in manuscript | 14,255 |
2409.01583v2 | On the anisotropic Calderón's problem | We prove that the Riemannian metric on a compact manifold of dimension $n\geq 3$ with smooth boundary can be uniquely determined, up to an isometry fixing the boundary, by the Dirichlet-to-Neumann map associated to the Laplace-Beltrami operator. | Analysis of PDEs (math.AP) | The argument is incorrect | factual/methodological/other critical errors in manuscript | 14,256 |
astro-ph/0503025v2 | The Outward Radial Offset of Neptune Ring Arcs | The designation of the customary restricted three-body disturbing potential $\Phi$ as the perturbation Hamiltonian is believed to be the cause of Neptune ring arcs' radial offset between theories and observations. To identify the appropriate perturbation Hamiltonian, the energy integral in the fixed frame of a restricted three-body system, consisting of the central, primary, and test bodies, is reconsidered. It is shown that the perturbation energy includes the disturbing potential $\Phi$ and the potential arising from the angular momentum terms of the test body. Both potentials happen to be singular as the test body goes to infinity contradicting to the perturbation nature. These two potentials can be combined to an energy relevant disturbing potential $\Phi^{*}=\beta\Phi$ which is regular at infinity because of the cancellation of the singularities. For circular orbits of the primary, the energy equation is conservative, and $\Phi^{*}$ is identified as the perturbation Hamiltonian. Applying this result to evaluate the backgrund effect of Triton to the arc-Galatea system of Neptune, it is shown that there is a small difference $\Delta\Phi=(\Phi^{*}-\Phi)$ which amounts to an outward radial offset of the corotation location of Galatea by 0.3 Km. The mismatch between the pattern speed of Galatea's corotation potential and the mean motion velocity of the arcs could be resolved by considering the finite mass of Fraternite. However, by using $\Phi^{*}$, Galatea's eccentricity could be reassessed in terms of the mass of Fraternite. | Astrophysics (astro-ph) | I have come to the conclusion that the model was not correct | factual/methodological/other critical errors in manuscript | 14,267 |
cond-mat/0110189v4 | Human Genome data analyzed by an evolutionary method suggests a decrease in cerebral protein-synthesis rate as cause of schizophrenia and an increase as antipsychotic mechanism | The Human Genome Project (HGP) provides researchers with the data of nearly all human genes and the challenge to use this information for elucidating the etiology of common disorders. A secondary Darwinian method was applied to HGP and other research data to approximate and possibly unravel the etiology of schizophrenia. The results indicate that genetic and epigenetic variants of genes involved in signal transduction, transcription and translation - converging at the protein-synthesis rate (PSR) as common final pathway - might be responsible for the genetic susceptibility to schizophrenia. Environmental (e.g. viruses)and/or genetic factors can lead to cerebral PSR (CPSR) deficiency. The CPSR hypothesis of schizophrenia and antipsychotic mechanism explains 96% of the major facts of schizophrenia, reveals links between previously unrelated facts, integrates many hypotheses, and implies that schizophrenia should be easily preventable and treatable, partly by immunization against neurotrophic viruses and partly by the development of new drugs which selectively increase CPSR. Part of the manuscript has been published in a modified form as "The glial growth factors deficiency and synaptic destabilization hypothesis of schizophrenia" in BMC Psychiatry available online at this http URL | Disordered Systems and Neural Networks (cond-mat.dis-nn) | This paper has been withdrawn by the author because it was largely based on a significant association of our schizophrenia sample with the genetic marker D8S1777. According to the available gene maps of the early [REDACTED-NAME] Project in 2000, the EIF4EBP1 gene was within range of that locus, but later versions of the HGP showed that the NRG1 gene actually mapped to this locus | factual/methodological/other critical errors in manuscript | 14,280 |
cond-mat/0310441v2 | Transport properties in Manganites | Transport properties in doped manganites are studied by considering the Simplified double exchange mechanism in the presence of diagonal disorder. It is modelled by a combination the Ising double exchange with Faliccov-Kimball model. In this model, charge order ferromagnetic and transport quantities are presented by using Dynamical mean-field theory in the case of finite Hund coupling and disorder strength. Those results suggest that, within this model the insulator phase can be stated in the range of below charge order temperature which is suitable with the observations in the experimental manganites. | Strongly Correlated Electrons (cond-mat.str-el) | This paper has been withdrawn by the author due to a crucial sign error in equation (13-15) | factual/methodological/other critical errors in manuscript | 14,287 |
cond-mat/0404160v2 | Evidence of a Macroscopic-Flux Phase in an Asymmetric Quantum Well in a Tilted Quantizing Magnetic Field | We demonstrate experimentally that in an asymmetric quantum well in presence of quantizing magnetic field tilted in XZ plane, confining potential V(z) lifts Landau level degeneracy related to position of the centers of electron cyclotron orbits along X axis. This results in arising of specific bands in which directed velocity of electrons along Y axis may be nonzero. We directly demonstrate that the electrons' velocity is in a one-to-one correspondence with the position of the centers of their cyclotron orbits that means spatially separated macroscopic electron fluxes should flow in opposite directions along Y axis even in the fully occupied bands. One-dimensional character of these fluxes is also demonstrated experimentally. | Mesoscale and Nanoscale Physics (cond-mat.mes-hall) | This paper has been withdrawn by the author because further experiments show incorrectness of the proposed interpretation. | factual/methodological/other critical errors in manuscript | 14,291 |
cond-mat/0404352v2 | Scaling dependence on time and distance in nonlinear fractional diffusion equations and possible applications to the water transport in soils | Recently, fractional derivatives have been employed to analyze various systems in engineering, physics, finance and hidrology. For instance, they have been used to investigate anomalous diffusion processes which are present in different physical systems like: amorphous semicondutors, polymers, composite heterogeneous films and porous media. They have also been used to calculate the heat load intensity change in blast furnace walls, to solve problems of control theory \ and dynamic problems of linear and nonlinear hereditary mechanics of solids. In this work, we investigate the scaling properties related to the nonlinear fractional diffusion equations and indicate the possibilities to the applications of these equations to simulate the water transport in unsaturated soils. Usually, the water transport in soils with anomalous diffusion, the dependence of concentration on time and distance may be expressed in term of a single variable given by $\lambda_q = x/t^{q}.$ In particular, for $q=1/2$ the systems obey Fick's law and Richards' equation for water transport. We show that a generalization of Richards' equation via fractional approach can incorporate the above property. | Soft Condensed Matter (cond-mat.soft) | The manuscript contains some errors | factual/methodological/other critical errors in manuscript | 14,292 |
cond-mat/0408381v2 | Experimental Evidence of a Directed-Flux Phase of Condensed Matter | We demonstrate experimentally that in an asymmetric quantum well in presence of quantizing magnetic field tilted in XZ plane, confining potential V(z) lifts Landau level degeneracy related to position of the centers of electron cyclotron orbits along X axis. This results in a transformation of the Landau levels into the bands in which the electrons may possess nonzero directed velocity along Y axis. We directly demonstrate that the electrons are spatially separated along X axis depending on their velocity along Y axis that means spontaneous one-dimensional electron fluxes flow in opposite directions along Y axis even within the fully occupied bands. We also directly demonstrate that the electrons possess nonzero electric dipole moment as a result of Lorentz force effect on these one-dimensional fluxes. On the basis of these experiments we put forward the concept of a directed-flux phase of condensed matter. | Mesoscale and Nanoscale Physics (cond-mat.mes-hall) | This paper has been withdrawn by the author because further experiments show incorrectness of the proposed interpretation. | factual/methodological/other critical errors in manuscript | 14,295 |
cond-mat/0410115v3 | Suppression of the anti-symmetry channel in the conductance of telescoped double-wall nanotubes | The conductance of telescoped double-wall nanotubes (TDWNTs) composed of two armchair nanotubes ($(n_O, n_O)$ and $(n_O-5, n_O-5)$ with $n_O \geq 10$) is calculated using the Landauer formula and a tight binding model. The results are in good agreement with the conductance calculated analytical by replacing each single-wall nanotube with a ladder, as expressed by $(2e^2/h)(T_+ + T_-)$, where $T_+$ and $T_-$ are the transmission rates of the symmetry and anti-symmetry channels, respectively. Perfect transmission in both channels is possible in this TDWNT when $n_O=10$, while $T_-$ is considerably small in the other TDWNTs. $T_-$ is particularly low when either $n_O$ or $n_O-5$ is a multiple of three. In this case, a three body effect of covalent-like interlayer bonds plays a crucial role in determining the finite $T_-$. When $n_O$ is a multiple of five, the five-fold symmetry increases $T_-$, although this effect diminishes with increasing $n_O$. | Mesoscale and Nanoscale Physics (cond-mat.mes-hall) | Owing to errors of the calculation code, the numerical data shown in Figures are incorrect. Nonetheless, the corrected numerical calculations do not change the essential results. See erratum, PHYSICAL REVIEW B 79, 199902 (2009). The responsibility for the errors lies completely with the first author ([REDACTED-NAME]) | factual/methodological/other critical errors in manuscript | 14,297 |
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