RecaLLM: Addressing the Lost-in-Thought Phenomenon with Explicit In-Context Retrieval

Kyle Whitecross, Negin Rahimi

We propose RecaLLM, a set of reasoning language models post-trained to make effective use of long-context information. In-context retrieval, which identifies relevant evidence from…