Evaluating Very Long-Term Conversational Memory of LLM Agents
Paper
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2402.17753
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Published
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18
llms for me
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StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
Paper • 2402.16671 • Published • 26 -
Do Large Language Models Latently Perform Multi-Hop Reasoning?
Paper • 2402.16837 • Published • 24 -
Divide-or-Conquer? Which Part Should You Distill Your LLM?
Paper • 2402.15000 • Published • 22 -
Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
Paper • 2402.14848 • Published • 18 -
AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning
Paper • 2402.15506 • Published • 13 -
OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
Paper • 2402.14658 • Published • 82 -
AgentScope: A Flexible yet Robust Multi-Agent Platform
Paper • 2402.14034 • Published • 12 -
Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming
Paper • 2402.14261 • Published • 10 -
User-LLM: Efficient LLM Contextualization with User Embeddings
Paper • 2402.13598 • Published • 18 -
Coercing LLMs to do and reveal (almost) anything
Paper • 2402.14020 • Published • 12 -
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 10 -
GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements
Paper • 2402.10963 • Published • 9 -
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
Paper • 2402.10379 • Published • 29 -
Large Language Models as Zero-shot Dialogue State Tracker through Function Calling
Paper • 2402.10466 • Published • 16 -
RLVF: Learning from Verbal Feedback without Overgeneralization
Paper • 2402.10893 • Published • 10 -
Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 99
ReGAL: Refactoring Programs to Discover Generalizable Abstractions
Paper • 2401.16467 • Published • 9Note 增加代码模板可以提高代码生成的准确性和稳定性
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Capture the Flag: Uncovering Data Insights with Large Language Models
Paper • 2312.13876 • Published • 1 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 65 -
Recourse for reclamation: Chatting with generative language models
Paper • 2403.14467 • Published • 6 -
AllHands: Ask Me Anything on Large-scale Verbatim Feedback via Large Language Models
Paper • 2403.15157 • Published • 7 -
Can large language models explore in-context?
Paper • 2403.15371 • Published • 32 -
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 44 -
Long-context LLMs Struggle with Long In-context Learning
Paper • 2404.02060 • Published • 35 -
Octopus v2: On-device language model for super agent
Paper • 2404.01744 • Published • 57 -
Long-form factuality in large language models
Paper • 2403.18802 • Published • 24 -
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 53 -
Scaling Instructable Agents Across Many Simulated Worlds
Paper • 2404.10179 • Published • 26 -
How Far Can We Go with Practical Function-Level Program Repair?
Paper • 2404.12833 • Published • 6 -
INDUS: Effective and Efficient Language Models for Scientific Applications
Paper • 2405.10725 • Published • 32 -
TextGrad: Automatic "Differentiation" via Text
Paper • 2406.07496 • Published • 26