VLDB talk: DR Tulu trains deep research agents with rubrics to pick BM25 or vector retrievers
CShorten30 · x · 2026-09-05
- Cites Akari Asai's VLDB talk covering two deep research agent training efforts:
- DR Tulu: trains deep research agents with rubrics to choose between BM25 and vector search retrievers, with strong results.
- AgentIR: trains a dedicated embedding model for the agent's intermediate reasoning and search queries.
- The author suggests combining AgentIR with BM25/ColBERT-style feedback — a meet-in-the-middle between searching by rationale and what the search returns.
- The retweeter notes how basic Deep Research, cutting-edge in early 2025, already looks — a sign of how fast the field iterates.
Related event: VLDB talk: Deep Research agents need co-designed retrievers(4 posts)→
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