Inter-Passage Verification for Multi-evidence Multi-answer QA (2025.findings-acl)
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| Challenge: | Existing multi-answer question answering systems struggle to retrieve and synthesize a large number of evidence passages. |
| Approach: | They propose a multi-answer question answering framework that generates a large set of passages and then processes each passage individually to generate an initial high-recall but noisy answer set. |
| Outcome: | The proposed framework outperforms baselines on the QAMPARI and RoMQA datasets, achieving an average F1 score improvement of 11.17%. |
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