COT-Reading-List

基础论文

• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models https://arxiv.org/abs/2201.11903
• Large Language Models are Zero-Shot Reasoners https://arxiv.org/abs/2205.11916
• Automatic Chain of Thought Prompting in Large Language Models https://arxiv.org/abs/2210.03493

问题分解

• Least-to-Most Prompting Enables Complex Reasoning in Large Language Models https://arxiv.org/abs/2205.10625
• Measuring and Narrowing the Compositionality Gap in Language Models https://arxiv.org/abs/2210.03350

融合预测

• Self-Consistency Improves Chain of Thought Reasoning in Language Models https://arxiv.org/abs/2203.11171
• Active Prompting with Chain-of-Thought for Large Language Models https://arxiv.org/abs/2302.12246
• Rationale-Augmented Ensembles in Language Models https://arxiv.org/abs/2207.00747

生成-校验

• STaR: Self-Taught Reasoner Bootstrapping Reasoning With Reasoning https://arxiv.org/abs/2203.14465
• On the Advance of Making Language Models Better Reasoners https://arxiv.org/abs/2206.02336

多语言

• Language Models are Multilingual Chain-of-Thought Reasoners https://arxiv.org/abs/2210.03057

大模型背景

• PaLM: Scaling Language Modeling with Pathways https://arxiv.org/abs/2204.02311
• Emergent Abilities of Large Language Models https://arxiv.org/abs/2206.07682
• Language Model Cascades https://arxiv.org/abs/2207.10342

2022.10.24