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Verifying textual claims against structured tabular data is a critical yet challenging task in Natural Language Processing with broad real-world impact. While recent advances in Large Language Models (LLMs) have enabled significant progress in table fact-checking, current solutions remain inaccessible to non-experts. We introduce T-REX (Table – Refute or Entail eXplainer), the first live, interactive tool for claim verification over multimodal, multilingual tables using state-of-the-art instruction-tuned reasoning LLMs. Designed for accuracy and transparency, T-REX empowers non-experts by providing access to advanced fact-checking technology. The system is openly available online. Online Demo: https://t-rex.r2.enst.fr Demo (video): https://www.youtube.com/watch?v=HHIxVCOT8X0 Github: https://github.com/TimLukaHorstmann/T-REX

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T-REX: Table – Refute or Entail eXplainer

  • 会议论文

  • 发表日期：

    2026年

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  • Tim Luka Horstmann,
  • Baptiste Geisenberger,
  • Mehwish Alam

摘要

Verifying textual claims against structured tabular data is a critical yet challenging task in Natural Language Processing with broad real-world impact. While recent advances in Large Language Models (LLMs) have enabled significant progress in table fact-checking, current solutions remain inaccessible to non-experts. We introduce T-REX (Table – Refute or Entail eXplainer), the first live, interactive tool for claim verification over multimodal, multilingual tables using state-of-the-art instruction-tuned reasoning LLMs. Designed for accuracy and transparency, T-REX empowers non-experts by providing access to advanced fact-checking technology. The system is openly available online. Online Demo: https://t-rex.r2.enst.fr Demo (video): https://www.youtube.com/watch?v=HHIxVCOT8X0 Github: https://github.com/TimLukaHorstmann/T-REX