Add new SentenceTransformer model

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 768,
+  "pooling_mode_cls_token": true,
+  "pooling_mode_mean_tokens": false,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

@@ -0,0 +1,603 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:9702
+- loss:TripletLoss
+base_model: sentence-transformers/allenai-specter
+widget:
+- source_sentence: The class of algorithmically computable simple games (i) includes
+    the class of games that have finite carriers and (ii) is included in the class
+    of games that have finite winning coalitions. This paper characterizes computable
+    games, strengthens the earlier result that computable games violate anonymity,
+    and gives examples showing that the above inclusions are strict. It also extends
+    Nakamura's theorem about the nonemptyness of the core and shows that computable
+    games have a finite Nakamura number, implying that the number of alternatives
+    that the players can deal with rationally is restricted.
+  sentences:
+  - We are going to study the limiting spectral measure of fixed dimensional Hermitian
+    block-matrices with large dimensional Wigner blocks. We are going also to identify
+    the limiting spectral measure when the Hermitian block-structure is Circulant.
+    Using the limiting spectral measure of a Hermitian Circulant block-matrix we will
+    show that the spectral measure of a Wigner matrix with $k-$weakly dependent entries
+    need not to be the semicircle law in the limit.
+  - The scope of the present study is Eulerian modeling and simulation of polydisperse
+    liquid sprays undergoing droplet coalescence and evaporation. The fundamental
+    mathematical description is the Williams spray equation governing the joint number
+    density function f(v, u; x, t) of droplet volume and velocity. Eulerian multi-fluid
+    models have already been rigorously derived from this equation in Laurent et al.
+    (2004). The first key feature of the paper is the application of direct quadrature
+    method of moments (DQMOM) introduced by Marchisio and Fox (2005) to the Williams
+    spray equation. Both the multi-fluid method and DQMOM yield systems of Eulerian
+    conservation equations with complicated interaction terms representing coalescence.
+    In order to validate and compare these approaches, the chosen configuration is
+    a self-similar 2D axisymmetrical decelerating nozzle with sprays having various
+    size distributions, ranging from smooth ones up to Dirac delta functions. The
+    second key feature of the paper is a thorough comparison of the two approaches
+    for various test-cases to a reference solution obtained through a classical stochastic
+    Lagrangian solver. Both Eulerian models prove to describe adequately spray coalescence
+    and yield a very interesting alternative to the Lagrangian solver.
+  - Recently, the iterative approach named linear tabling has received considerable
+    attention because of its simplicity, ease of implementation, and good space efficiency.
+    Linear tabling is a framework from which different methods can be derived based
+    on the strategies used in handling looping subgoals. One decision concerns when
+    answers are consumed and returned. This paper describes two strategies, namely,
+    {\it lazy} and {\it eager} strategies, and compares them both qualitatively and
+    quantitatively. The results indicate that, while the lazy strategy has good locality
+    and is well suited for finding all solutions, the eager strategy is comparable
+    in speed with the lazy strategy and is well suited for programs with cuts. Linear
+    tabling relies on depth-first iterative deepening rather than suspension to compute
+    fixpoints. Each cluster of inter-dependent subgoals as represented by a top-most
+    looping subgoal is iteratively evaluated until no subgoal in it can produce any
+    new answers. Naive re-evaluation of all looping subgoals, albeit simple, may be
+    computationally unacceptable. In this paper, we also introduce semi-naive optimization,
+    an effective technique employed in bottom-up evaluation of logic programs to avoid
+    redundant joins of answers, into linear tabling. We give the conditions for the
+    technique to be safe (i.e. sound and complete) and propose an optimization technique
+    called {\it early answer promotion} to enhance its effectiveness. Benchmarking
+    in B-Prolog demonstrates that with this optimization linear tabling compares favorably
+    well in speed with the state-of-the-art implementation of SLG.
+- source_sentence: We survey recent progress on the Greenfield-Wallach and Katok conjectures
+    on globally hypoelliptic and cohomology free vector fields and derive a proof
+    of the conjectures in dimension three. The argument is primarily based on recent
+    work of F. and J. Rodriguez Hertz which allows us to reduce the question to the
+    case of a Reeb flow for a contact form. The contact case is settled by invoking
+    the Weinstein conjecture (which has been recently announced by C. Taubes).
+  sentences:
+  - We describe several views of the semantics of a simple programming language as
+    formal documents in the calculus of inductive constructions that can be verified
+    by the Coq proof system. Covered aspects are natural semantics, denotational semantics,
+    axiomatic semantics, and abstract interpretation. Descriptions as recursive functions
+    are also provided whenever suitable, thus yielding a a verification condition
+    generator and a static analyser that can be run inside the theorem prover for
+    use in reflective proofs. Extraction of an interpreter from the denotational semantics
+    is also described. All different aspects are formally proved sound with respect
+    to the natural semantics specification.
+  - Zero-divisors (ZDs) derived by Cayley-Dickson Process (CDP) from N-dimensional
+    hypercomplex numbers (N a power of 2, at least 4) can represent singularities
+    and, as N approaches infinite, fractals -- and thereby,scale-free networks. Any
+    integer greater than 8 and not a power of 2 generates a meta-fractal or "Sky"
+    when it is interpreted as the "strut constant" (S) of an ensemble of octahedral
+    vertex figures called "Box-Kites" (the fundamental building blocks of ZDs). Remarkably
+    simple bit-manipulation rules or "recipes" provide tools for transforming one
+    fractal genus into others within the context of Wolfram's Class 4 complexity.
+  - The purpose of this paper is to determine the asymptotic of the average energy
+    of a configuration of N zeros of system of random polynomials of degree N as N
+    tends to infinity and more generally the zeros of random holomorphic sections
+    of a line bundle L over any Riemann surface M. And we compare our results to the
+    well-known minimum of energies.
+- source_sentence: How do blogs cite and influence each other? How do such links evolve?
+    Does the popularity of old blog posts drop exponentially with time? These are
+    some of the questions that we address in this work. Our goal is to build a model
+    that generates realistic cascades, so that it can help us with link prediction
+    and outlier detection. Blogs (weblogs) have become an important medium of information
+    because of their timely publication, ease of use, and wide availability. In fact,
+    they often make headlines, by discussing and discovering evidence about political
+    events and facts. Often blogs link to one another, creating a publicly available
+    record of how information and influence spreads through an underlying social network.
+    Aggregating links from several blog posts creates a directed graph which we analyze
+    to discover the patterns of information propagation in blogspace, and thereby
+    understand the underlying social network. Not only are blogs interesting on their
+    own merit, but our analysis also sheds light on how rumors, viruses, and ideas
+    propagate over social and computer networks. Here we report some surprising findings
+    of the blog linking and information propagation structure, after we analyzed one
+    of the largest available datasets, with 45,000 blogs and ~ 2.2 million blog-postings.
+    Our analysis also sheds light on how rumors, viruses, and ideas propagate over
+    social and computer networks. We also present a simple model that mimics the spread
+    of information on the blogosphere, and produces information cascades very similar
+    to those found in real life.
+  sentences:
+  - We present a suite of programs to determine the ground state of the time-independent
+    Gross-Pitaevskii equation, used in the simulation of Bose-Einstein condensates.
+    The calculation is based on the Optimal Damping Algorithm, ensuring a fast convergence
+    to the true ground state. Versions are given for the one-, two-, and three-dimensional
+    equation, using either a spectral method, well suited for harmonic trapping potentials,
+    or a spatial grid.
+  - We propose a method to perform precision measurements of the interaction parameters
+    in systems of N ultra-cold spin 1/2 atoms. The spectroscopy is realized by first
+    creating a coherent spin superposition of the two relevant internal states of
+    each atom and then letting the atoms evolve under a squeezing Hamiltonian. The
+    non-linear nature of the Hamiltonian decreases the fundamental limit imposed by
+    the Heisenberg uncertainty principle to N^(-2), a factor of N smaller than the
+    fundamental limit achievable with non-interacting atoms. We study the effect of
+    decoherence and show that even with decoherence, entangled states can outperform
+    the signal to noise limit of non-entangled states. We present two possible experimental
+    implementations of the method using Bose-Einstein spinor condensates and fermionic
+    atoms loaded in optical lattices and discuss their advantages and disadvantages.
+  - Bivariate linear mixed models are useful when analyzing longitudinal data of two
+    associated markers. In this paper, we present a bivariate linear mixed model including
+    random effects or first-order auto-regressive process and independent measurement
+    error for both markers. Codes and tricks to fit these models using SAS Proc MIXED
+    are provided. Limitations of this program are discussed and an example in the
+    field of HIV infection is shown. Despite some limitations, SAS Proc MIXED is a
+    useful tool that may be easily extendable to multivariate response in longitudinal
+    studies.
+- source_sentence: The effect of the magnetic field on the critical behavior of Sr0:9La0:1CuO2
+    is explored in terms of reversible magnetization data. As the correlation length
+    transverse to the magnetic field Hi,applied along the i-axis, cannot grow beyond
+    the limiting magnetic length LHi, related to the average distance between vortex
+    lines, one expects a magnetic field induced finite size effect. Invoking the scaling
+    theory of critical phenomena we provide clear evidence for this effect. It implies
+    that in type II superconductors there is a 3D to 1D crossover line Hpi(T). Consequently,
+    below Tc and above Hpi(T) uperconductivity is confined to cylinders with diameter
+    LHi(1D). Accordingly, there is no continuous phase transition in the (H,T)-plane
+    along the Hc2-lines as predicted by the mean-field treatment.
+  sentences:
+  - We introduce a new construction, the isotropy groupoid, to organize the orbit
+    data for split $\Gamma$-spaces. We show that equivariant principal $G$-bundles
+    over split $\Gamma$-CW complexes $X$ can be effectively classified by means of
+    representations of their isotropy groupoids. For instance, if the quotient complex
+    $A=\Gamma\backslash X$ is a graph, with all edge stabilizers toral subgroups of
+    $\Gamma$, we obtain a purely combinatorial classification of bundles with structural
+    group $G$ a compact connected Lie group. If $G$ is abelian, our approach gives
+    combinatorial and geometric descriptions of some results of Lashof-May-Segal and
+    Goresky-Kottwitz-MacPherson.
+  - We analyze 27 house price indexes of Las Vegas from Jun. 1983 to Mar. 2005, corresponding
+    to 27 different zip codes. These analyses confirm the existence of a real-estate
+    bubble, defined as a price acceleration faster than exponential, which is found
+    however to be confined to a rather limited time interval in the recent past from
+    approximately 2003 to mid-2004 and has progressively transformed into a more normal
+    growth rate comparable to pre-bubble levels in 2005. There has been no bubble
+    till 2002 except for a medium-sized surge in 1990. In addition, we have identified
+    a strong yearly periodicity which provides a good potential for fine-tuned prediction
+    from month to month. A monthly monitoring using a model that we have developed
+    could confirm, by testing the intra-year structure, if indeed the market has returned
+    to ``normal'' or if more turbulence is expected ahead. We predict the evolution
+    of the indexes one year ahead, which is validated with new data up to Sep. 2006.
+    The present analysis demonstrates the existence of very significant variations
+    at the local scale, in the sense that the bubble in Las Vegas seems to have preceded
+    the more global USA bubble and has ended approximately two years earlier (mid
+    2004 for Las Vegas compared with mid-2006 for the whole of the USA).
+  - The use of off-resonant standing light waves to manipulate ultracold atoms is
+    investigated. Previous work has illustrated that optical pulses can provide efficient
+    beam-splitting and reflection operations for atomic wave packets. The performance
+    of these operations is characterized experimentally using Bose-Einstein condensates
+    confined in a weak magnetic trap. Under optimum conditions, fidelities of up to
+    0.99 for beam splitting and 0.98 for reflection are observed, and splitting operations
+    of up to third order are achieved. The dependence of the operations on light intensity
+    and atomic velocity is measured and found to agree well with theoretical estimates.
+- source_sentence: Let G be a free group in a variety of groups, but G is not absolutely
+    free. We prove that the group of automorphisms Aut(G) is linear iff G is a virtually
+    nilpotent group.
+  sentences:
+  - An orthogonal array OA(q^{2n-1},q^{2n-2}, q,2) is constructed from the action
+    of a subset of PGL(n+1,q^2) on some non--degenerate Hermitian varieties in PG(n,q^2).
+    It is also shown that the rows of this orthogonal array correspond to some blocks
+    of an affine design, which for q> 2 is a non--classical model of the affine space
+    AG(2n-1,q).
+  - We describe a new universality class for unitary invariant random matrix ensembles.
+    It arises in the double scaling limit of ensembles of random $n \times n$ Hermitian
+    matrices $Z_{n,N}^{-1} |\det M|^{2\alpha} e^{-N \Tr V(M)} dM$ with $\alpha > -1/2$,
+    where the factor $|\det M|^{2\alpha}$ induces critical eigenvalue behavior near
+    the origin. Under the assumption that the limiting mean eigenvalue density associated
+    with $V$ is regular, and that the origin is a right endpoint of its support, we
+    compute the limiting eigenvalue correlation kernel in the double scaling limit
+    as $n, N \to \infty$ such that $n^{2/3}(n/N-1) = O(1)$. We use the Deift-Zhou
+    steepest descent method for the Riemann-Hilbert problem for polynomials on the
+    line orthogonal with respect to the weight $|x|^{2\alpha} e^{-NV(x)}$. Our main
+    attention is on the construction of a local parametrix near the origin by means
+    of the $\psi$-functions associated with a distinguished solution of the Painleve
+    XXXIV equation. This solution is related to a particular solution of the Painleve
+    II equation, which however is different from the usual Hastings-McLeod solution.
+  - 'Suppose that a target function is monotonic, namely, weakly increasing, and an
+    original estimate of the target function is available, which is not weakly increasing.
+    Many common estimation methods used in statistics produce such estimates. We show
+    that these estimates can always be improved with no harm using rearrangement techniques:
+    The rearrangement methods, univariate and multivariate, transform the original
+    estimate to a monotonic estimate, and the resulting estimate is closer to the
+    true curve in common metrics than the original estimate. We illustrate the results
+    with a computational example and an empirical example dealing with age-height
+    growth charts.'
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+metrics:
+- cosine_accuracy
+model-index:
+- name: SentenceTransformer based on sentence-transformers/allenai-specter
+  results:
+  - task:
+      type: triplet
+      name: Triplet
+    dataset:
+      name: triplet eval
+      type: triplet_eval
+    metrics:
+    - type: cosine_accuracy
+      value: 0.9319999814033508
+      name: Cosine Accuracy
+    - type: cosine_accuracy
+      value: 0.9399999976158142
+      name: Cosine Accuracy
+---
+
+# SentenceTransformer based on sentence-transformers/allenai-specter
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/allenai-specter](https://huggingface.co/sentence-transformers/allenai-specter). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [sentence-transformers/allenai-specter](https://huggingface.co/sentence-transformers/allenai-specter) <!-- at revision 2c68eeca61259b2dd70c3f2628219f925df7031a -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 768 dimensions
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
+  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("nadrajak/allenai-specter-ft")
+# Run inference
+sentences = [
+    'Let G be a free group in a variety of groups, but G is not absolutely free. We prove that the group of automorphisms Aut(G) is linear iff G is a virtually nilpotent group.',
+    'An orthogonal array OA(q^{2n-1},q^{2n-2}, q,2) is constructed from the action of a subset of PGL(n+1,q^2) on some non--degenerate Hermitian varieties in PG(n,q^2). It is also shown that the rows of this orthogonal array correspond to some blocks of an affine design, which for q> 2 is a non--classical model of the affine space AG(2n-1,q).',
+    'Suppose that a target function is monotonic, namely, weakly increasing, and an original estimate of the target function is available, which is not weakly increasing. Many common estimation methods used in statistics produce such estimates. We show that these estimates can always be improved with no harm using rearrangement techniques: The rearrangement methods, univariate and multivariate, transform the original estimate to a monotonic estimate, and the resulting estimate is closer to the true curve in common metrics than the original estimate. We illustrate the results with a computational example and an empirical example dealing with age-height growth charts.',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 768]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Triplet
+
+* Dataset: `triplet_eval`
+* Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
+
+| Metric              | Value     |
+|:--------------------|:----------|
+| **cosine_accuracy** | **0.932** |
+
+#### Triplet
+
+* Dataset: `triplet_eval`
+* Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
+
+| Metric              | Value    |
+|:--------------------|:---------|
+| **cosine_accuracy** | **0.94** |
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 9,702 training samples
+* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | anchor                                                                               | positive                                                                             | negative                                                                             |
+  |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
+  | type    | string                                                                               | string                                                                               | string                                                                               |
+  | details | <ul><li>min: 37 tokens</li><li>mean: 175.25 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 172.87 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 162.78 tokens</li><li>max: 451 tokens</li></ul> |
+* Samples:
+  | anchor                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | negative                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
+  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>We study the notion of the scaled entropy of a filtration of $\sigma$-fields (= decreasing sequence of $\sigma$-fields) introduced by the first author ({V4}). We suggest a method for computing this entropy for the sequence of $\sigma$-fields of pasts of a Markov process determined by a random walk over the trajectories of a Bernoulli action of a commutative or nilpotent countable group (Theorems~5,~6). Since the scaled entropy is a metric invariant of the filtration, it follows that the sequences of $\sigma$-fields of pasts of random walks over the trajectories of Bernoulli actions of lattices (groups ${\Bbb Z}^d$) are metrically nonisomorphic for different dimensions $d$, and for the same $d$ but different values of the entropy of the Bernoulli scheme. We give a brief survey of the metric theory of filtrations, in particular, formulate the standardness criterion and describe its connections with the scaled entropy and the notion of a tower of measures.</code>                                     | <code>In this paper we complete a classification of finite linear spaces $\cS$ with line size at most 12 admitting a line-transitive point-imprimitive subgroup of automorphisms. The examples are the Desarguesian projective planes of orders $4,7, 9$ and 11, two designs on 91 points with line size 6, and 467 designs on 729 points with line size 8.</code>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       | <code>We show that the combined data from solar, long-baseline and reactor neutrino experiments can exclude the generalized bicycle model of Lorentz noninvariant direction-dependent and/or direction-independent oscillations of massless neutrinos. This model has five parameters, which is more than is needed in standard oscillation phenomenology with neutrino masses. Solar data alone are sufficient to exclude the pure direction-dependent case. The combination of solar and long-baseline data rules out the pure direction-independent case. With the addition of KamLAND data, a mixture of direction-dependent and direction-independent terms in the effective Hamiltonian is also excluded.</code>  |
+  | <code>We discuss a numerical model for black hole growth and its associated feedback processes that for the first time allows cosmological simulations of structure formation to self-consistently follow the build up of the cosmic population of galaxies and active galactic nuclei. Our model assumes that seed black holes are present at early cosmic epochs at the centres of forming halos. We then track their growth from gas accretion and mergers with other black holes in the course of cosmic time. For black holes that are active, we distinguish between two distinct modes of feedback, depending on the black hole accretion rate itself. Black holes that accrete at high rates are assumed to be in a `quasar regime', where we model their feedback by thermally coupling a small fraction of their bolometric luminosity to the surrounding gas. For black holes with low accretion rates, we conjecture that most of their feedback occurs in mechanical form, where AGN-driven bubbles are injected into a gaseous e...</code> | <code>Context: L'-band (3.8 micron) images of the Galactic Center show a large number of thin filaments in the mini-spiral, located west of the mini-cavity and along the inner edge of the Northern Arm. One possible mechanism that could produce such structures is the interaction of a central wind with the mini-spiral. Additionally, we identify similar features that appear to be associated with stars. Aims: We present the first proper motion measurements of the thin dust filaments observed in the central parsec around SgrA* and investigate possible mechanisms that could be responsible for the observed motions. Methods: The observations have been carried out using the NACO adaptive optics system at the ESO VLT. The images have been transformed to a common coordinate system and features of interest were extracted. Then a cross-correlation technique could be performed in order to determine the offsets between the features with respect to their position in the reference epoch. Results: We derive t...</code> | <code>Energy resolution, alpha/beta ratio, pulse-shape discrimination for gamma rays and alpha particles, temperature dependence of scintillation properties, and radioactive contamination were studied with CaMoO4 crystal scintillators. A high sensitivity experiment to search for neutrinoless double beta decay of 100-Mo by using CaMoO4 scintillators is discussed.</code>                                                                                                                                                                                                                                                                                                                                     |
+  | <code>From a macroscopic point of view phase transitions as surface melting or two dimensional (2D) towards three dimensional (3D) growth mode (Stranski-Krastanov transition) can be described in terms of Gibbs excess quantity duly amended by size effects (since usual Gibbs excess quantities are only well defined for semi-infinite systems). The aim of this study is to consider such amended quantities to describe surface melting and Stranski-Krastanov transition of epitaxial layers. the so-introduced size effects allows us to predict the equilibrium thickness of the wetting layer of the Stranski-Krastanov growth mode and to describe and classify two different melting cases: the incomplete melting relayed by a first order transition and the continuous premelting relayed by continuous overheating</code>                                                                                                                                                                                                               | <code>We tailor the shape and phase of the pump pulse spectrum in order to study the coherent lattice dynamics in tellurium. Employing the coherent control via splitting the pump pulse into a two-pulse sequence, we show that the oscillations due to A1 coherent phonons can be cancelled but not enhanced as compared to single pulse excitation. We further demonstrate that a decisive factor for the coherent phonon generation is the bandwidth of the pulse spectrum and not the steepness of the pulse envelope. We also observe that the coherent amplitude for long pump pulses decreases exponentially independent of the shape of the pulse spectrum. Finally, by varying the pulse chirp, we show that the coherent amplitude is independent of while the oscillation lifetime is dependent on the chirp sign.</code>                                                                                                                                                                                                                    | <code>From the spectral plot of the (normalized) graph Laplacian, the essential qualitative properties of a network can be simultaneously deduced. Given a class of empirical networks, reconstruction schemes for elucidating the evolutionary dynamics leading to those particular data can then be developed. This method is exemplified for protein-protein interaction networks. Traces of their evolutionary history of duplication and divergence processes are identified. In particular, we can identify typical specific features that robustly distinguish protein-protein interaction networks from other classes of networks, in spite of possible statistical fluctuations of the underlying data.</code> |
+* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
+  ```json
+  {
+      "distance_metric": "TripletDistanceMetric.EUCLIDEAN",
+      "triplet_margin": 5
+  }
+  ```
+
+### Evaluation Dataset
+
+#### Unnamed Dataset
+
+* Size: 2,389 evaluation samples
+* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | anchor                                                                               | positive                                                                            | negative                                                                             |
+  |:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
+  | type    | string                                                                               | string                                                                              | string                                                                               |
+  | details | <ul><li>min: 39 tokens</li><li>mean: 169.07 tokens</li><li>max: 485 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 168.4 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 165.13 tokens</li><li>max: 478 tokens</li></ul> |
+* Samples:
+  | anchor                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           | negative                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
+  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>We give axioms which characterize the local Reidemeister trace for orientable differentiable manifolds. The local Reidemeister trace in fixed point theory is already known, and we provide both uniqueness and existence results for the local Reidemeister trace in coincidence theory.</code>                                                                                                                                                                                                                                                                                                                     | <code>We derive a unified stochastic picture for the duality of a resampling-selection model with a branching-coalescing particle process (cf. http://www.ams.org/mathscinet-getitem?mr=MR2123250) and for the self-duality of Feller's branching diffusion with logistic growth (cf. math/0509612). The two dual processes are approximated by particle processes which are forward and backward processes in a graphical representation. We identify duality relations between the basic building blocks of the particle processes which lead to the two dualities mentioned above.</code>                                                                                                                                                                                                                                                       | <code>CLIC is a linear $e^+e^-$ ($\gamma\gamma$) collider project which uses a drive beam to accelerate the main beam. The drive beam provides RF power for each corresponding unit of the main linac through energy extracting RF structures. CLIC has a wide range of center-of-mass energy options from 150 GeV to 3 TeV. The present paper contains optimization of Free Electron Laser (FEL) using one bunch of CLIC drive beam in order to provide polarized light amplification using appropriate wiggler and luminosity spectrum of $\gamma\gamma$ collider for $E_{cm}$=0.5 TeV. Then amplified laser can be converted to a polarized high-energy $\gamma$ beam at the Conversion point (CP-prior to electron positron interaction point) in the process of Compton backscattering. At the CP a powerful laser pulse (FEL) focused to main linac electrons (positrons). Here this scheme described and it is show that CLIC drive beam parameters satisfy the requirement of FEL additionally essential undulator parameters has been...</code> |
+  | <code>We determine the quantum phase diagram of the one-dimensional Hubbard model with bond-charge interaction X in addition to the usual Coulomb repulsion U at half-filling. For large enough X and positive U the model shows three phases. For large U the system is in the spin-density wave phase already known in the usual Hubbard model. As U decreases, there is first a spin transition to a spontaneously dimerized bond-ordered wave phase and then a charge transition to a novel phase in which the dominant correlations at large distances correspond to an incommensurate singlet superconductor.</code> | <code>Vortex-antivortex pairs are localized excitations and have been found to be spontaneously created in magnetic elements. In the case that the vortex and the antivortex have opposite polarities the pair has a nonzero topological charge, and it behaves as a rotating vortex dipole. We find theoretically, and confirm numerically, the form of the energy as a function of the angular momentum of the system and the associated rotation frequencies. We discuss the process of annihilation of the pair which changes the topological charge of the system by unity while its energy is monotonically decreasing. Such a change in the topological charge affects profoundly the dynamics in the magnetic system. We finally discuss the connection of our results with Bloch Points (BP) and the implications for BP dynamics.</code> | <code>We present results of simulations of a muon content in the air showers induced by very high energy cosmic rays. Muon energy distributions and muon densities at ground level are given. We discuss a prompt muon component generated by decays of charm mesons. The method combines standard Monte Carlo generators incorporated in the CORSIKA code and phenomenological estimates of the charm hadroproduction.</code>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
+  | <code>We discuss quantum evolution of a decaying state in relation to a recent experiment of Katz et al. Based on exact analytical and numerical solutions of a simple model, we identify a regime where qubit retains coherence over a finite time interval independently of the rates of three competing decoherence processes. In this regime, the quantum decay process can be continuously monitored via a ``weak'' measurement without affecting the qubit coherence.</code>                                                                                                                                         | <code>We investigate the physical property of the kappa parameter and the kappa-distribution in the kappa-deformed statistics, based on Kaniadakis entropy, for a relativistic gas in an electromagnetic field. We derive two relations for the relativistic gas in the framework of kappa-deformed statistics, which describe the physical situation represented by the relativistic kappa-distribution function, provide a reasonable connection between the parameter kappa, the temperature four-gradient and the four-vector potential gradient, and thus present for the case kappa different from zero a clearly physical meaning. It is shown that such a physical situation is a meta-equilibrium state of the system, but has a new physical characteristic.</code>                                                                      | <code>We analyze 27 house price indexes of Las Vegas from Jun. 1983 to Mar. 2005, corresponding to 27 different zip codes. These analyses confirm the existence of a real-estate bubble, defined as a price acceleration faster than exponential, which is found however to be confined to a rather limited time interval in the recent past from approximately 2003 to mid-2004 and has progressively transformed into a more normal growth rate comparable to pre-bubble levels in 2005. There has been no bubble till 2002 except for a medium-sized surge in 1990. In addition, we have identified a strong yearly periodicity which provides a good potential for fine-tuned prediction from month to month. A monthly monitoring using a model that we have developed could confirm, by testing the intra-year structure, if indeed the market has returned to ``normal'' or if more turbulence is expected ahead. We predict the evolution of the indexes one year ahead, which is validated with new data up to Sep. 2006. The present...</code> |
+* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
+  ```json
+  {
+      "distance_metric": "TripletDistanceMetric.EUCLIDEAN",
+      "triplet_margin": 5
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `learning_rate`: 2e-05
+- `warmup_ratio`: 0.1
+- `fp16`: True
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 8
+- `per_device_eval_batch_size`: 8
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 2e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 3
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: True
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss | Validation Loss | triplet_eval_cosine_accuracy |
+|:------:|:----:|:-------------:|:---------------:|:----------------------------:|
+| -1     | -1   | -             | -               | 0.8210                       |
+| 0.4122 | 500  | 1.4856        | 1.2697          | 0.8910                       |
+| 0.8244 | 1000 | 0.897         | 0.9961          | 0.9250                       |
+| 1.2366 | 1500 | 0.5647        | 1.0038          | 0.9210                       |
+| 1.6488 | 2000 | 0.3959        | 0.8957          | 0.9330                       |
+| 2.0610 | 2500 | 0.3289        | 0.8055          | 0.9220                       |
+| 2.4732 | 3000 | 0.1267        | 0.7920          | 0.9290                       |
+| 2.8854 | 3500 | 0.096         | 0.8040          | 0.9320                       |
+| -1     | -1   | -             | -               | 0.9400                       |
+
+
+### Framework Versions
+- Python: 3.11.13
+- Sentence Transformers: 4.1.0
+- Transformers: 4.52.4
+- PyTorch: 2.6.0+cu124
+- Accelerate: 1.8.1
+- Datasets: 2.14.4
+- Tokenizers: 0.21.2
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### TripletLoss
+```bibtex
+@misc{hermans2017defense,
+    title={In Defense of the Triplet Loss for Person Re-Identification},
+    author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
+    year={2017},
+    eprint={1703.07737},
+    archivePrefix={arXiv},
+    primaryClass={cs.CV}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,25 @@
+{
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31116
+}

config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "4.1.0",
+    "transformers": "4.52.4",
+    "pytorch": "2.6.0+cu124"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:121fdd666ce81b1b022cf239dfa23242915ccbba653d6c6edd2b94586673db7f
+size 439776096

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,58 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}