🔄 TL;DR: A search index that diagnoses its own weaknesses, rewrites its keys, and validates the changes — all without any human in the loop. It beats existing methods by a wide margin on BRIGHT. Title: Self-Evolving Search Index URL: Points 🩺 Builds co-retrieval profiles from search results to self-diagnose whether documents are well distinguished, with no human annotation needed ✍️ Selectively revises key sets only for flagged documents, autonomously deciding up to 10 keys per document ✅ Self-validates proposals on faithfulness, specificity, and separation, keeping only keys that pass 🔍 A Query Simulator proactively probes uncovered demand with synthetic queries 📈 Hits 22.8 average nDCG@10 on BRIGHT, +9.2% over RL-Index and +40-57% over the base index 🤖 For search agents, answer accuracy jumps +77.87% while search calls drop -16.80% The idea of making index optimization itself self-evolving, not just the model or the agent, is what makes this interesting. #InformationRetrieval# #LLMAgents#