mlsanityData to 14 Oct 2026

TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance

arXiv 2105.07624 ↗First posted 17 May 2021cs.CL cs.AIcited by 408

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Cited by 84 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Hybrid data combining both tabular and textual content (e.g., financial reports) are quite pervasive in the real world. However, Question Answering (QA) over such hybrid data is largely neglected in existing research. In this work, we extract samples from real financial reports to build a new large-scale QA dataset containing both Tabular And Textual data, named TAT-QA, where numerical reasoning is usually required to infer the answer, such as addition, subtraction, multiplication, division, counting, comparison/sorting, and the compositions. We further propose a novel QA model termed TAGOP, which is capable of reasoning over both tables and text. It adopts sequence tagging to extract relevant cells from the table along with relevant spans from the text to infer their semantics, and then applies symbolic reasoning over them with a set of aggregation operators to arrive at the final answer. TAGOPachieves 58.0% inF1, which is an 11.1% absolute increase over the previous best baseline model, according to our experiments on TAT-QA. But this result still lags far behind performance of expert human, i.e.90.8% in F1. It is demonstrated that our TAT-QA is very challenging and can serve as a benchmark for training and testing powerful QA models that address hybrid form data.

Key facts. Cited by 408 papers in the map (data through 14 Oct 2026). Builds on 27 of its 41 references that are in the map. First posted on arXiv 17 May 2021.

Builds on

27 of 41 references.

References · 27

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,148
  4. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,754
  5. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,139
  6. 2015Teaching Machines to Read and Comprehendcited by 1,049
  7. 2019DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphscited by 903
  8. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 687
  9. 2015Compositional Semantic Parsing on Semi-Structured Tablescited by 515
  10. 2020TAPAS: Weakly Supervised Table Parsing via Pre-trainingcited by 434
  11. 2018The Web as a Knowledge-base for Answering Complex Questionscited by 410
  12. 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 398
15 more
  1. 2020HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Datacited by 264
  2. 2017Constructing Datasets for Multi-hop Reading Comprehension Across Documentscited by 190
  3. 2019PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Textcited by 184
  4. 2021Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answeringcited by 178
  5. 2020Open Question Answering over Tables and Textcited by 163
  6. 2020Molweni: A Challenge Multiparty Dialogues-based Machine Reading Comprehension Dataset with Discourse Structurecited by 60
  7. 2019NumNet: Machine Reading Comprehension with Numerical Reasoningcited by 59
  8. 2019Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehensioncited by 51
  9. 2016Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answeringcited by 35
  10. 2020Question Directed Graph Attention Network for Numerical Reasoning over Textcited by 35
  11. 2020Summarizing and Exploring Tabular Data in Conversational Searchcited by 19
  12. 2018Explicit State Tracking with Semi-Supervision for Neural Dialogue Generationcited by 17
  13. 2017Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networkscited by 15
  14. 2019Auto-completion for Data Cells in Relational Tablescited by 9
  15. 2016A deep learning approach for predicting the quality of online health expert question-answering servicescited by 4

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Citing papers per year: 2021: 6; 2022: 34; 2023: 34; 2024: 88; 2025: 104; 2026: 142.

408 papers.

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  1. 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Taskscited by 1,076
  2. 2024Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMscited by 838
  3. 2022Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoningcited by 350
  4. 2024What matters when building vision-language models?cited by 326
  5. 2023FinanceBench: A New Benchmark for Financial Question Answeringcited by 270
  6. 2022Making Large Language Models Better Reasoners with Step-Aware Verifiercited by 233
  7. 2024RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMscited by 202
  8. 2022ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answeringcited by 196
  9. 2023TheoremQA: A Theorem-driven Question Answering datasetcited by 192
  10. 2025MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipecited by 186
  11. 2023Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Futurecited by 184
  12. 2024Building and better understanding vision-language models: insights and future directionscited by 173
38 more
  1. 2024Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Surveycited by 159
  2. 2023Active Prompting with Chain-of-Thought for Large Language Modelscited by 154
  3. 2024FinBen: A Holistic Financial Benchmark for Large Language Modelscited by 141
  4. 2024TableBench: A Comprehensive and Complex Benchmark for Table Question Answeringcited by 128
  5. 2024MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scalecited by 127
  6. 2022A Survey of Deep Learning for Mathematical Reasoningcited by 124
  7. 2022MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Datacited by 121
  8. 2021HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generationcited by 118
  9. 2024RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systemscited by 117
  10. 2022Large Language Models are few(1)-shot Table Reasonerscited by 116
  11. 2023Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaborationcited by 116
  12. 2024SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulationcited by 111
  13. 2024The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Modelscited by 93
  14. 2024HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extractioncited by 93
  15. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
  16. 2024ChatQA: Surpassing GPT-4 on Conversational QA and RAGcited by 90
  17. 2025ReFocus: Visual Editing as a Chain of Thought for Structured Image Understandingcited by 83
  18. 2022Towards Complex Document Understanding By Discrete Reasoningcited by 82
  19. 2024A Survey of Large Language Models in Finance (FinLLMs)cited by 79
  20. 2024TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarioscited by 77
  21. 2023Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaborationcited by 70
  22. 2024Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Datacited by 63
  23. 2024DocFinQA: A Long-Context Financial Reasoning Datasetcited by 60
  24. 2023A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagramcited by 56
  25. 2024FinTextQA: A Dataset for Long-form Financial Question Answeringcited by 54
  26. 2025FineVision: Open Data Is All You Needcited by 53
  27. 2023RCOT: Detecting and Rectifying Factual Inconsistency in Reasoning by Reversing Chain-of-Thoughtcited by 47
  28. 2024A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Taskscited by 47
  29. 2024Financial Report Chunking for Effective Retrieval Augmented Generationcited by 46
  30. 2022Reasoning Like Program Executorscited by 45
  31. 2022PACIFIC: Towards Proactive Conversational Question Answering over Tabular and Textual Data in Financecited by 45
  32. 2023DocMath-Eval: Evaluating Math Reasoning Capabilities of LLMs in Understanding Long and Specialized Documentscited by 45
  33. 2021AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industrycited by 44
  34. 2024Multimodal Table Understandingcited by 44
  35. 2025StockBench: Can LLM Agents Trade Stocks Profitably In Real-world Markets?cited by 44
  36. 2024On the Multi-turn Instruction Following for Conversational Web Agentscited by 43
  37. 2022Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Taskscited by 42
  38. 2024PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makerscited by 42

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