Deng, X., Wang, X. and Stevenson, R. orcid.org/0000-0002-9483-6006 (Accepted: 2025) +VeriRel: Verification feedback to enhance document retrieval for scientific fact checking. In: Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM'25). 34th ACM International Conference on Information and Knowledge Management (CIKM'25), 10-14 Nov 2025, Seoul, Korea. ACM. ISBN: 9798400720406/2025/11. (In Press)
Abstract
Identification of appropriate supporting evidence is critical to the success of scientific fact checking. However, existing approaches rely on off-the-shelf Information Retrieval algorithms that rank documents based on relevance rather than the evidence they provide to support or refute the claim being checked. This paper proposes +VeriRel which includes verification success in the document ranking. Experimental results on three scientific fact checking datasets (SciFact, SciFact-Open and Check-Covid) demonstrate consistently leading performance by +VeriRel for document evidence retrieval and a positive impact on downstream verification. This study highlights the potential of integrating verification feedback to document relevance assessment for effective scientific fact checking systems. It shows promising future work to evaluate fine-grained relevance when examining complex documents for advanced scientific fact checking.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 Copyright held by the owner/author(s). |
Keywords: | Evidence retrieval; Scientific fact checking; Document ranking |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Sep 2025 14:18 |
Last Modified: | 05 Sep 2025 14:18 |
Status: | In Press |
Publisher: | ACM |
Refereed: | Yes |
Identification Number: | 10.1145/3746252.3760822 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:231102 |