Conversational Query Reformulation (CQR) can be improved by leveraging key information extracted from initially retrieved documents to generate more retriever-friendly queries.
IterCQR iteratively trains a conversational query reformulation model without human-annotated rewrites, utilizing retrieval signals as a reward to generate queries optimized for off-the-shelf retrievers.