Contextual Drag: How Errors in the Context Affect LLM Reasoning

Yun Cheng, Xingyu Zhu, Haoyu Zhao +1

Central to many self-improvement pipelines for large language models (LLMs) is the assumption that models can improve by reflecting on past mistakes. We study a phenomenon termed c…