T-REX: Table -- Refute or Entail eXplainer

Tim Luka Horstmann, Baptiste Geisenberger, Mehwish Alam
8/8/2025
cs.CLcs.AI

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Abstract

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 (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.

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Cite this paper

@article{horstmann2025trex,
  title  = {T-REX: Table -- Refute or Entail eXplainer},
  author = {Tim Luka Horstmann and Baptiste Geisenberger and Mehwish Alam},
  year   = {2025},
  eprint = {2508.14055},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.14055v1}
}

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