Papers by Riyaz Ahmad Bhat
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. |
XTR meets ColBERTv2: Adding ColBERTv2 Optimizations to XTR (2025.coling-industry)
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| Challenge: | XTR eliminates the need for multi-stage retrieval, but doesn't incorporate efficiency optimizations from ColBERTv2 which improve indexing and retrieval speed. |
| Approach: | They propose a multi-vector retrieval method that simplifies retrieval into a single stage through a modified learning objective. |
| Outcome: | The proposed method eliminates the need for multistage retrieval but doesn't incorporate efficiency optimizations from ColBERTv2 which improve indexing and retrieval speed. |