mlsanityData to 7 Oct 2026

SemEval-2021 Task 9: Fact Verification and Evidence Finding for Tabular Data in Scientific Documents (SEM-TAB-FACTS)

arXiv 2105.13995 ↗First posted 28 May 2021cs.CLcited by 35

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Abstract (arXiv)

Understanding tables is an important and relevant task that involves understanding table structure as well as being able to compare and contrast information within cells. In this paper, we address this challenge by presenting a new dataset and tasks that addresses this goal in a shared task in SemEval 2020 Task 9: Fact Verification and Evidence Finding for Tabular Data in Scientific Documents (SEM-TAB-FACTS). Our dataset contains 981 manually-generated tables and an auto-generated dataset of 1980 tables providing over 180K statement and over 16M evidence annotations. SEM-TAB-FACTS featured two sub-tasks. In sub-task A, the goal was to determine if a statement is supported, refuted or unknown in relation to a table. In sub-task B, the focus was on identifying the specific cells of a table that provide evidence for the statement. 69 teams signed up to participate in the task with 19 successful submissions to subtask A and 12 successful submissions to subtask B. We present our results and main findings from the competition.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). Builds on 12 of its 25 references that are in the map. First posted on arXiv 28 May 2021.

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12 of 25 references.

References · 12

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  3. 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,665
  4. 2015A large annotated corpus for learning natural language inferencecited by 1,837
  5. 2015Compositional Semantic Parsing on Semi-Structured Tablescited by 509
  6. 2020TAPAS: Weakly Supervised Table Parsing via Pre-trainingcited by 432
  7. 2019TabFact: A Large-scale Dataset for Table-based Fact Verificationcited by 425
  8. 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 395
  9. 2020INFOTABS: Inference on Tables as Semi-structured Datacited by 84
  10. 2019SemEval-2019 Task 8: Fact Checking in Community Question Answering Forumscited by 18
  11. 2021TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-trainingcited by 14
  12. 2021BreakingBERT@IITK at SemEval-2021 Task 9 : Statement Verification and Evidence Finding with Tablescited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 4; 2023: 6; 2024: 8; 2025: 8; 2026: 5.

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  1. 2021A Survey on Automated Fact-Checkingcited by 376
  2. 2023FactKG: Fact Verification via Reasoning on Knowledge Graphscited by 57
  3. 2023SCITAB: A Challenging Benchmark for Compositional Reasoning and Claim Verification on Scientific Tablescited by 51
  4. 2022PASTA: Table-Operations Aware Fact Verification via Sentence-Table Cloze Pre-trainingcited by 41
  5. 2023Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checkingcited by 34
  6. 2023TempTabQA: Temporal Question Answering for Semi-Structured Tablescited by 27
  7. 2024CABINET: Content Relevance based Noise Reduction for Table Question Answeringcited by 23
  8. 2024Claim Verification in the Age of Large Language Models: A Surveycited by 23
  9. 2024GraphOTTER: Evolving LLM-based Graph Reasoning for Complex Table Question Answeringcited by 18
  10. 2022Table-based Fact Verification with Self-adaptive Mixture of Expertscited by 12
  11. 2024ClaimVer: Explainable Claim-Level Verification and Evidence Attribution of Text Through Knowledge Graphscited by 11
  12. 2025CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?cited by 11
23 more
  1. 2025SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrievalcited by 11
  2. 2024TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoningcited by 10
  3. 2025Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challengescited by 10
  4. 2021Is My Model Using The Right Evidence? Systematic Probes for Examining Evidence-Based Tabular Reasoningcited by 9
  5. 2024Knowledge-Aware Reasoning over Multimodal Semi-structured Tablescited by 9
  6. 2025MuSciClaims: Multimodal Scientific Claim Verificationcited by 8
  7. 2022Optimization Techniques for Unsupervised Complex Table Reasoning via Self-Training Frameworkcited by 6
  8. 2023Evaluating Concurrent Robustness of Language Models Across Diverse Challenge Setscited by 6
  9. 2026SciClaimEval: Cross-modal Claim Verification in Scientific Paperscited by 6
  10. 2021Logic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact Verificationcited by 4
  11. 2025Table-Text Alignment: Explaining Claim Verification Against Tables in Scientific Paperscited by 4
  12. 2022Leveraging Data Recasting to Enhance Tabular Reasoningcited by 3
  13. 2023INO at Factify 2: Structure Coherence based Multi-Modal Fact Verificationcited by 3
  14. 2024EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Recordscited by 3
  15. 2025Task-Oriented Automatic Fact-Checking with Frame-Semanticscited by 3
  16. 2026ClaimDB: A Fact Verification Benchmark over Large Structured Datacited by 3
  17. 2021TabPert: An Effective Platform for Tabular Perturbationcited by 2
  18. 2025What to Keep and What to Drop: Adaptive Table Filtering Frameworkcited by 1
  19. 2025PanelTR: Zero-Shot Table Reasoning Framework Through Multi-Agent Scientific Discussioncited by 1
  20. 2026Analyzing LLM Instruction Optimization for Tabular Fact Verificationcited by 1
  21. 2024Bridging Textual and Tabular Worlds for Fact Verification: A Lightweight, Attention-Based Modelcited by 0
  22. 2026Frame-Guided Synthetic Claim Generation for Automatic Fact-Checking Using High-Volume Tabular Datacited by 0
  23. 2026A Multi-Agent Approach for Claim Verification from Tabular Data Documentscited by 0