DARE-RAG: Difficulty-Aware Retrieval Expansion for Retrieval-Augmented Generation
DARE-RAG is proposed, an adaptive retrieval framework that activates LLM-based query expansion only for retrieval-challenging queries, and formulates expansion activation as a lightweight binary classification problem using probe retrieval signals, including score margin, variance, entropy, query length, and lexical specificity.