TimelyRAG: Semantic-Temporal Hybrid Retrieval for Time-Critical Question Answering in Overlapping-Evolving Documents

• URL: http://arxiv.org/abs/2609.11572v1
• Date: Thu, 10 Sep 2026 14:07:20 GMT
• Title: TimelyRAG: Semantic-Temporal Hybrid Retrieval for Time-Critical Question Answering in Overlapping-Evolving Documents
• Abstract summary: TimelyRAG is a retriever-agnostic framework that incorporates temporal distance into ranking to align queries with version-appropriate documents.<n>We also introduce TimelyQABench, the first benchmark for regulation-heavy domains with overlapping-evolving challenges.
• Score: 32.19368966069081
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Although large language models (LLMs) and retrieval-augmented generation (RAG) have advanced open-domain question answering (QA), they remain unreliable when documents evolve through amendments. Existing time-sensitive retrieval methods address only the disjoint-evolving environment, where each update is an independent snapshot. However, laws, policies, and regulations often operate in overlapping-evolving environments, where amendments override earlier clauses while preserving most content, creating strong semantic overlap across versions. We propose TimelyRAG, a retriever-agnostic framework that incorporates temporal distance into ranking to align queries with version-appropriate documents. We also introduce TimelyQABench, the first benchmark for regulation-heavy domains with overlapping-evolving challenges. Experiments show consistent gains, up to +28.6% in nDCG@10, highlighting the importance of temporal reasoning for reliable QA over evolving documents. All resources are available at https://github.com/kaist-dmlab/TimelyRAG.

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