Howard University-AI4PC at SemEval-2025 Task 7: Crosslingual Fact-Checked Claim Retrieval-Combining Zero-Shot Claim Extraction and KNN-Based Classification for Multilingual Claim Matching

Suprabhat Rijal, Saurav Aryal


Abstract
SemEval Task 7 introduced a dataset for multilingual and cross-lingual fact checking. We propose a system that leverages similarity matching, KNN, zero-shot classification and summarization to retrieve fact-checks for social media posts across multiple languages. Our approach achieves performance within the expected range, aligning with baseline results. Although competitive, the findings highlight the potential and challenges of zero-shot methods, providing a foundation for future research in cross-lingual information verification.
Anthology ID:
2025.semeval-1.234
Volume:
Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Sara Rosenthal, Aiala Rosá, Debanjan Ghosh, Marcos Zampieri
Venues:
SemEval | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1777–1782
Language:
URL:
https://preview.aclanthology.org/transition-to-people-yaml/2025.semeval-1.234/
DOI:
Bibkey:
Cite (ACL):
Suprabhat Rijal and Saurav Aryal. 2025. Howard University-AI4PC at SemEval-2025 Task 7: Crosslingual Fact-Checked Claim Retrieval-Combining Zero-Shot Claim Extraction and KNN-Based Classification for Multilingual Claim Matching. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 1777–1782, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
Howard University-AI4PC at SemEval-2025 Task 7: Crosslingual Fact-Checked Claim Retrieval-Combining Zero-Shot Claim Extraction and KNN-Based Classification for Multilingual Claim Matching (Rijal & Aryal, SemEval 2025)
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https://preview.aclanthology.org/transition-to-people-yaml/2025.semeval-1.234.pdf