ru
ru
Source
ACL Workshop
DATE OF PUBLICATION
07/11/2025
Authors
Evgenii Nikolaev Ivan Bondarenko Islam Aushev Vasilii Krikunov Andrei Glinskii Vasily Konovalov Julia Belikova
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FactDebug at SemEval-2025 Task 7: Hybrid Retrieval Pipeline for Identifying Previously Fact-Checked Claims Across Multiple Languages

Abstract

The proliferation of multilingual misinformation demands robust systems for crosslingual fact-checked claim retrieval. This paper addresses SemEval-2025 Shared Task 7, which challenges participants to retrieve fact-checks for social media posts across 14 languages, even when posts and fact-checks are in different languages. We propose a hybrid retrieval pipeline that combines sparse lexical matching (BM25, BGE-m3) and dense semantic retrieval (pretrained and fine-tuned BGE-m3) with dynamic fusion and curriculum-trained rerankers. Our system achieves 67.2% crosslingual and 86.01% monolingual accuracy on the Shared Task MultiClaim dataset.

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