Kangshi Wang

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2025

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DKE-Research at SemEval-2025 Task 7: A Unified Multilingual Framework for Cross-Lingual and Monolingual Retrieval with Efficient Language-specific Adaptation
Yuqi Wang | Kangshi Wang
Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)

This paper presents a unified framework for fact-checked claim retrieval, integrating contrastive learning with an in-batch multiple negative ranking loss and a conflict-aware batch sampler to enhance query-document alignment across languages. Additionally, we introduce language-specific adapters for efficient fine-tuning, enabling adaptation to previously unseen languages.
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