Craig Macdonald

Predicting Partial Answer Quality and Utility in Agentic Retrieval-Augmented Generation

Agentic Retrieval-Augmented Generation (RAG) has become a promising paradigm for multi-hop question answering, where a reasoning model iteratively issues queries to a retriever and incorporates newly retrieved context into subsequent reasoning steps. While this iterative process can improve final answer quality, curren...