SOURCE-LINKED INTELLIGENCE
Q-TIE: A Lightweight and Generalizable Re-ranking Framework for Temporal Information Retrieval
Temporal Information Retrieval (TIR) has been increasingly critical given the rise of Retrieval-Augmented Generation (RAG). Since temporally mismatched evidence can be highly misleading, TIR aims to retrieve documents that are both semantically and temporally relevant to a query. Two TIR paradigms have emerged - temporal retrievers and temporal re-rankers - differing in how temporal relevance is modeled. While these paradigms provide complementary strengths, our analysis reveals that each alone falls short of robust TIR: temporal retrievers provide flexible query understanding via learned repr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-20T21:30:31.000Z
First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.