Papers by Yucheng Tian
R^3AG: Retriever Routing for Retrieval-Augmented Generation (2026.acl-long)
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| Challenge: | Retrieval-augmented generation (RAG) is often bottlenecked by the “one-size-fits-all” retrieval paradigm, as different queries exhibit distinct preferences for different retrievers. |
| Approach: | They propose a novel routing framework that explicitly models the dynamic alignment between queries and retriever capabilities and decomposes retriever capability into two learnable dimensions: retrieval quality and generation utility. |
| Outcome: | Experiments on knowledge-intensive tasks show that R3AG outperforms both the best individual retrievers and state-of-the-art static routing methods. |