Papers with downstream modeling
Revealing the Importance of Semantic Retrieval for Machine Reading at Scale (D19-1)
Copied to clipboard
| Challenge: | Recent advances in representation learning have separated progress in both IR and MC . few studies have examined the relationship between retrieval and comprehension at different levels of granularity for development of MRS systems. |
| Approach: | They propose a simple yet effective pipeline system with consideration on hierarchical semantic retrieval at both paragraph and sentence level and their potential effects on the downstream task. |
| Outcome: | The proposed system achieves state-of-the-art on the leaderboard test sets of both FEVER and HOTPOTQA. |
DualAlign: Generating Clinically Grounded Synthetic Data (2026.findings-acl)
Copied to clipboard
| Challenge: | Large language models (LLMs) can generate fluent clinical text, but ensuring that such outputs are clinically grounded and useful for downstream modeling remains challenging. |
| Approach: | They propose a disease-agnostic framework for generating privacy-preserving, clinically faithful synthetic EHR narratives. |
| Outcome: | The proposed framework produces context-aware, symptom-rich sentences that more closely reflect real-world clinical documentation. |