Orca 2: Teaching Small Language Models How to Reason
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2311.11045
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Published
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71
LLM-Reasoning
Note prompt erasing
Learning From Mistakes Makes LLM Better Reasoner
Paper • 2310.20689 • Published • 28Note 在COT数据的基础上，增加【错误步骤的评语】+【修正的结果】进行训练
Let's Verify Step by Step
Paper • 2305.20050 • Published • 10Note Outcome-supervised RM与Process-supervised RM
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SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Paper • 2308.00436 • Published • 22 -
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Paper • 2310.11511 • Published • 75 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 11 -
Let's Reinforce Step by Step
Paper • 2311.05821 • Published • 1 -
TinyGSM: achieving >80% on GSM8k with small language models
Paper • 2312.09241 • Published • 37 -
ProTIP: Progressive Tool Retrieval Improves Planning
Paper • 2312.10332 • Published • 7 -
The Impact of Reasoning Step Length on Large Language Models
Paper • 2401.04925 • Published • 16 -
Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 104 -
Iterative Reasoning Preference Optimization
Paper • 2404.19733 • Published • 47 -
Mixture-of-Instructions: Comprehensive Alignment of a Large Language Model through the Mixture of Diverse System Prompting Instructions
Paper • 2404.18410 • Published -
NumLLM: Numeric-Sensitive Large Language Model for Chinese Finance
Paper • 2405.00566 • Published -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 113 -
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Paper • 2406.12050 • Published • 19 -
Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement
Paper • 2310.08559 • Published • 1 -
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Paper • 2406.18629 • Published • 41