Papers by Suraj Nair
Cross-language Sentence Selection via Data Augmentation and Rationale Training (2021.acl-long)
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| Challenge: | a new approach to cross-language sentence selection is proposed for low-resource contexts . a cross-lingual embedding-based model is proposed that avoids translation entirely . |
| Approach: | They propose a cross-lingual embedding-based query relevance model that uses data augmentation and negative sampling techniques to directly learn a query-sentence pair. |
| Outcome: | The proposed approach performs better than state-of-the-art models on noisy parallel data . consistent improvements are seen across three language pairs over state- of-the art models . |
A Representation Sharpening Framework for Zero Shot Dense Retrieval (2026.eacl-long)
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| Challenge: | Zero-shot dense retrieval requires generic, pretrained DRs, which struggle to represent semantic differences between similar documents. |
| Approach: | They propose a training-free representation sharpening framework that augments a document’s representation with information that helps differentiate it from similar documents in the corpus. |
| Outcome: | The proposed framework is compatible with prior approaches to zero-shot dense retrieval and consistently improves their performance. |