Papers by Serwar Basch
ABCD-LINK: Annotation Bootstrapping for Cross-Document Fine-Grained Links (2026.eacl-long)
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| Challenge: | Using retrieval models and LLMs achieves a 73% approval rate for suggested links, more than doubling the acceptance of strong retrievers alone. |
| Approach: | They propose a domain-agnostic framework for bootstrapping sentence-level cross-document links from scratch and apply it to large-scale human-in-the-loop annotation of natural text pairs. |
| Outcome: | The proposed framework generates semi-synthetic datasets and uses them to benchmark and shortlist the best-performing methods and applies them in large-scale human-in-the-loop annotation of natural text pairs. |
User-Centric Evidence Ranking for Attribution and Fact Verification (2026.eacl-long)
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| Challenge: | Large language models often present users with insufficient or redundant information, leading to inefficient and error-prone verification. |
| Approach: | They propose a task that prioritizes presenting sufficient information as early as possible in a ranked list. |
| Outcome: | The proposed task minimizes user reading effort while making all available evidence accessible for sequential verification. |