Papers by Vignesh P

1 papers
UR2N: Unified Retriever and ReraNker (2025.coling-industry)

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Challenge: XTR-style retrieval on top of trained Mono-T5 reranker is suboptimal for two-stage retrieval, arguing that it is sub-optimal.
Approach: They propose a unified encoder-decoder architecture with a novel training regimen which enables the encoder representation to be used for retrieval and the decoder for re-ranking within a single unified model.
Outcome: The proposed architecture outperforms ColBERT, XTR, and even serves as a superior reranker compared to the Mono-T5 re-ranker.

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