# T-REX: Table -- Refute or Entail eXplainer

arXiv: https://arxiv.org/abs/2508.14055 · HTML: https://mlsanity.com/paper/2508.14055/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 6 references that are in the map.
- First posted on arXiv 8 Aug 2025.

## Builds on (most cited first, 5 of 5)

- [TabFact: A Large-scale Dataset for Table-based Fact Verification](https://mlsanity.com/paper/1909.02164/) (2019)
- [Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning](https://mlsanity.com/paper/2301.13808/) (2023)
- [RePanda: Pandas-powered Tabular Verification and Reasoning](https://mlsanity.com/paper/2503.11921/) (2025)
- [ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics](https://mlsanity.com/paper/2412.14146/) (2024)
- ["The Data Says Otherwise"-Towards Automated Fact-checking and Communication of Data Claims](https://mlsanity.com/paper/2409.10713/) (2024)

## Abstract (arXiv)

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.