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Collections including paper arxiv:2402.06457

Papers - Coding - Fine-tuning

V-STaR: Training Verifiers for Self-Taught Reasoners

Paper • 2402.06457 • Published Feb 9 • 8
Advancing LLM Reasoning Generalists with Preference Trees

Paper • 2404.02078 • Published Apr 2 • 43
McEval: Massively Multilingual Code Evaluation

Paper • 2406.07436 • Published Jun 11 • 39
Is Programming by Example solved by LLMs?

Paper • 2406.08316 • Published Jun 12 • 11

Papers - Coding - Training

ReGAL: Refactoring Programs to Discover Generalizable Abstractions

Paper • 2401.16467 • Published Jan 29 • 8
V-STaR: Training Verifiers for Self-Taught Reasoners

Paper • 2402.06457 • Published Feb 9 • 8

Rethinking Optimization and Architecture for Tiny Language Models

Paper • 2402.02791 • Published Feb 5 • 12
More Agents Is All You Need

Paper • 2402.05120 • Published Feb 3 • 51
Scaling Laws for Forgetting When Fine-Tuning Large Language Models

Paper • 2401.05605 • Published Jan 11
Aligning Large Language Models with Counterfactual DPO

Paper • 2401.09566 • Published Jan 17 • 2

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Paper • 2312.04474 • Published Dec 7, 2023 • 29
Boosting LLM Reasoning: Push the Limits of Few-shot Learning with Reinforced In-Context Pruning

Paper • 2312.08901 • Published Dec 14, 2023
Learning From Mistakes Makes LLM Better Reasoner

Paper • 2310.20689 • Published Oct 31, 2023 • 28
Making Large Language Models Better Reasoners with Step-Aware Verifier

Paper • 2206.02336 • Published Jun 6, 2022 • 1

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