Self-Evolving Search Index
Information retrieval is increasingly important as LLM agents tackle complex tasks involving diverse information needs. Because retrieval relies on an index that represents each document through index keys, retrieval quality depends heavily on how effectively these keys expose the knowledge contained in each document. However, effective index representations vary across retrieval environments, making it difficult for any fixed optimization strategy to perform consistently. Yet evolving an index to its retrieval environment remains largely human-driven, requiring humans to diagnose retrieval failures, refine the optimization strategy, and reprocess the index accordingly. We propose SELF-IN...
| Authors | Sangam Lee, Wonjae Lee, Sunghwan Kim et al. |
|---|---|
| Primary category | cs.IR |
| Published | 17 September 2026 |
| Last updated at source | 17 September 2026 |
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