Papers by Martin Hyben
MultiCW: A Large-Scale Balanced Benchmark Dataset for Training Robust Check-Worthiness Detection Models (2026.findings-eacl)
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| Challenge: | Large language models (LLMs) are beginning to reshape how media professionals verify information, but support for detecting check-worthy claims remains limited. |
| Approach: | They propose a multilingual benchmark for check-worthy claim detection spanning 16 languages, six topical domains, and two writing styles. |
| Outcome: | The proposed model outperforms zero-shot LLMs on claim classification and strong generalization across languages, domains, and styles. |