Collections
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Collections including paper arxiv:2402.06457
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V-STaR: Training Verifiers for Self-Taught Reasoners
Paper • 2402.06457 • Published • 3 -
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 43 -
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 47
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V-STaR: Training Verifiers for Self-Taught Reasoners
Paper • 2402.06457 • Published • 3 -
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 43 -
McEval: Massively Multilingual Code Evaluation
Paper • 2406.07436 • Published • 39 -
Is Programming by Example solved by LLMs?
Paper • 2406.08316 • Published • 11
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Rethinking Optimization and Architecture for Tiny Language Models
Paper • 2402.02791 • Published • 12 -
More Agents Is All You Need
Paper • 2402.05120 • Published • 51 -
Scaling Laws for Forgetting When Fine-Tuning Large Language Models
Paper • 2401.05605 • Published -
Aligning Large Language Models with Counterfactual DPO
Paper • 2401.09566 • Published • 2
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The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs
Paper • 2210.14986 • Published • 4 -
Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2
Paper • 2311.10702 • Published • 18 -
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 75 -
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
Paper • 2309.04269 • Published • 32