Zuchen Zhuang

Difficulty-aware Dynamic Chain-of-Thought Prompting for Large Language Models via BM25 and Semantic Retrieval

A dynamic Chain-of-Thought prompting method based on problem difficulty assessment that effectively resolve the two major limitations of traditional exemplar-based methods, enabling LLMs to obtain appropriately tailored exemplars for both multi-step mathematical reasoning and interdisciplinary question answering.