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Communicative Agents for Software Development
Paper • 2307.07924 • Published • 4 -
Self-Refine: Iterative Refinement with Self-Feedback
Paper • 2303.17651 • Published • 2 -
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent
Paper • 2312.10003 • Published • 38 -
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 16
Collections
Discover the best community collections!
Collections including paper arxiv:2404.02575
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Compiler generated feedback for Large Language Models
Paper • 2403.14714 • Published • 5 -
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 48 -
Compiling C to Safe Rust, Formalized
Paper • 2412.15042 • Published • 1
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V-STaR: Training Verifiers for Self-Taught Reasoners
Paper • 2402.06457 • Published • 9 -
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 44 -
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 48
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ReGAL: Refactoring Programs to Discover Generalizable Abstractions
Paper • 2401.16467 • Published • 10 -
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 48 -
How Far Can We Go with Practical Function-Level Program Repair?
Paper • 2404.12833 • Published • 7
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Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
Paper • 2403.09029 • Published • 55 -
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 25 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 69 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 76
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 53 -
Beyond Language Models: Byte Models are Digital World Simulators
Paper • 2402.19155 • Published • 50 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 137 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 19
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 105 -
Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 46 -
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
Paper • 2403.10704 • Published • 58 -
MathScale: Scaling Instruction Tuning for Mathematical Reasoning
Paper • 2403.02884 • Published • 17
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 18 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 30 -
The Impact of Reasoning Step Length on Large Language Models
Paper • 2401.04925 • Published • 16
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GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 188 -
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 48 -
Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs
Paper • 2404.05719 • Published • 83 -
LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QA
Paper • 2409.02897 • Published • 45
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Creative Robot Tool Use with Large Language Models
Paper • 2310.13065 • Published • 9 -
CodeCoT and Beyond: Learning to Program and Test like a Developer
Paper • 2308.08784 • Published • 5 -
Lemur: Harmonizing Natural Language and Code for Language Agents
Paper • 2310.06830 • Published • 31 -
CodePlan: Repository-level Coding using LLMs and Planning
Paper • 2309.12499 • Published • 74