T-REX: Table -- Refute or Entail eXplainer
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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.
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.
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5 of 6 references.
References · 5
- 2019TabFact: A Large-scale Dataset for Table-based Fact Verificationcited by 428
- 2023Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoningcited by 178
- 2025RePanda: Pandas-powered Tabular Verification and Reasoningcited by 5
- 2024ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analyticscited by 4
- 2024"The Data Says Otherwise"-Towards Automated Fact-checking and Communication of Data Claimscited by 3
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- 2024TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning
- 2024TabVer: Tabular Fact Verification with Natural Logic
- 2025Table-Text Alignment: Explaining Claim Verification Against Tables in Scientific Papers
- 2025TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models
- 2025Towards Automated Fact-Checking of Real-World Claims: Exploring Task Formulation and Assessment with LLMs
- 2023Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models
- 2024TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition
- 2023EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification