mlsanityData to 7 Oct 2026

A Survey of Table Reasoning with Large Language Models

arXiv 2402.08259 ↗First posted 13 Feb 2024cs.CLcited by 29

On the map: LLM reasoning → Knowledge- and tool-augmented reasoning

Abstract (arXiv)

Table reasoning, which aims to generate the corresponding answer to the question following the user requirement according to the provided table, and optionally a text description of the table, effectively improving the efficiency of obtaining information. Recently, using Large Language Models (LLMs) has become the mainstream method for table reasoning, because it not only significantly reduces the annotation cost but also exceeds the performance of previous methods. However, existing research still lacks a summary of LLM-based table reasoning works. Due to the existing lack of research, questions about which techniques can improve table reasoning performance in the era of LLMs, why LLMs excel at table reasoning, and how to enhance table reasoning abilities in the future, remain largely unexplored. This gap significantly limits progress in research. To answer the above questions and advance table reasoning research with LLMs, we present this survey to analyze existing research, inspiring future work. In this paper, we analyze the mainstream techniques used to improve table reasoning performance in the LLM era, and the advantages of LLMs compared to pre-LLMs for solving table reasoning. We provide research directions from both the improvement of existing methods and the expansion of practical applications to inspire future research.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 76 of its 103 references that are in the map. First posted on arXiv 13 Feb 2024.

Builds on

76 of 103 references.

Closest ancestors · 11

Same direction, newest first

  1. 2024Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding9 Jan
  2. 2023Rethinking Tabular Data Understanding with Large Language Models27 Dec
  3. 2023Retrieval-Augmented Generation for Large Language Models: A Survey18 Dec
  4. 2023TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning14 Dec
  5. 2023On Evaluating the Integration of Reasoning and Action in LLM Agents with Database Question Answering16 Nov
  6. 2023ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thought26 Oct
  7. 2023Effective Distillation of Table-based Reasoning Ability from LLMs22 Sep
  8. 2023SCITAB: A Challenging Benchmark for Compositional Reasoning and Claim Verification on Scientific Tables22 May
  9. 2023Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning31 Jan
  10. 2022Large Language Models are few(1)-shot Table Reasoners13 Oct
  11. 2021HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation15 Aug

Other references · 65

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  3. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  4. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  5. 2023A Survey of Large Language Modelscited by 2,537
  6. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  7. 2023Large Language Models as Optimizerscited by 830
  8. 2023WizardCoder: Empowering Code Large Language Models with Evol-Instructcited by 728
  9. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 679
  10. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
  11. 2015Compositional Semantic Parsing on Semi-Structured Tablescited by 509
  12. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
38 more
  1. 2019TabFact: A Large-scale Dataset for Table-based Fact Verificationcited by 425
  2. 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 395
  3. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  4. 2021A Survey on Automated Fact-Checkingcited by 376
  5. 2023What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuningcited by 354
  6. 2022Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoningcited by 347
  7. 2023StructGPT: A General Framework for Large Language Model to Reason over Structured Datacited by 339
  8. 2022Generate rather than Retrieve: Large Language Models are Strong Context Generatorscited by 296
  9. 2023Large Language Models as Tool Makerscited by 293
  10. 2020ToTTo: A Controlled Table-To-Text Generation Datasetcited by 267
  11. 2022UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Modelscited by 231
  12. 2023LEVER: Learning to Verify Language-to-Code Generation with Executioncited by 228
  13. 2022Binding Language Models in Symbolic Languagescited by 224
  14. 2019Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representationcited by 210
  15. 2023Self-Evaluation Guided Beam Search for Reasoningcited by 195
  16. 2023RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLcited by 191
  17. 2019CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databasescited by 180
  18. 2021FeTaQA: Free-form Table Question Answeringcited by 174
  19. 2019SParC: Cross-Domain Semantic Parsing in Contextcited by 141
  20. 2023TableLlama: Towards Open Large Generalist Models for Tablescited by 136
  21. 2021Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Surveycited by 130
  22. 2023Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Studycited by 116
  23. 2021Towards Robustness of Text-to-SQL Models against Synonym Substitutioncited by 110
  24. 2021KaggleDBQA: Realistic Evaluation of Text-to-SQL Parserscited by 105
  25. 2020Logical Natural Language Generation from Open-Domain Tablescited by 90
  26. 2020INFOTABS: Inference on Tables as Semi-structured Datacited by 84
  27. 2023ReAcTable: Enhancing ReAct for Table Question Answeringcited by 76
  28. 2023Data Diversity Matters for Robust Instruction Tuningcited by 76
  29. 2024EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Recordscited by 75
  30. 2021Document AI: Benchmarks, Models and Applicationscited by 61
  31. 2020On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queriescited by 59
  32. 2022Data Curation Alone Can Stabilize In-context Learningcited by 58
  33. 2023Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMscited by 49
  34. 2021AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industrycited by 44
  35. 2022A Survey on Table Question Answering: Recent Advancescited by 41
  36. 2022OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answeringcited by 29
  37. 2021Awakening Latent Grounding from Pretrained Language Models for Semantic Parsingcited by 28
  38. 2023Large Language Models are Complex Table Parserscited by 28

50 most cited of 65 All 65 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 7; 2025: 15; 2026: 7.

29 papers.

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  1. 2024Large Language Models Meet NLP: A Surveycited by 102
  2. 2025SQL-o1: A Self-Reward Heuristic Dynamic Search Method for Text-to-SQLcited by 19
  3. 2025TableMaster: A Recipe to Advance Table Understanding with Language Modelscited by 18
  4. 2025SHARE: An SLM-based Hierarchical Action CorREction Assistant for Text-to-SQLcited by 15
  5. 2025Multimodal Tabular Reasoning with Privileged Structured Informationcited by 14
  6. 2024ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQLcited by 13
  7. 2024MiMoTable: A Multi-scale Spreadsheet Benchmark with Meta Operations for Table Reasoningcited by 12
  8. 2025Benchmarking Multimodal LLMs on Recognition and Understanding over Chemical Tablescited by 10
  9. 2024ALTER: Augmentation for Large-Table-Based Reasoningcited by 9
  10. 2024FLEXTAF: Enhancing Table Reasoning with Flexible Tabular Formatscited by 8
  11. 2025Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Modelscited by 7
  12. 2025Table as a Modality for Large Language Modelscited by 7
17 more
  1. 2025Mixture-of-Minds: Multi-Agent Reinforcement Learning for Table Understandingcited by 6
  2. 2025HIPPO: Enhancing the Table Understanding Capability of LLMs through Hybrid-Modal Preference Optimizationcited by 5
  3. 2025TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoningcited by 5
  4. 2024Using Large Language Models to Generate Clinical Trial Tables and Figurescited by 3
  5. 2025Formula-R1: Incentivizing LLM Reasoning over Complex Tables with Numerical Computation via Formula-Driven Reinforcement Learningcited by 3
  6. 2025TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Modelscited by 3
  7. 2025TableZoomer: A Collaborative Agent Framework for Large-scale Table Question Answeringcited by 3
  8. 2025Toward Real-World Table Agents: Capabilities, Workflows, and Design Principles for LLM-based Table Intelligencecited by 2
  9. 2026CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoningcited by 2
  10. 2026ReasonTabQA: A Comprehensive Benchmark for Table Question Answering from Real World Industrial Scenarioscited by 1
  11. 2024Can Language Models Enable In-Context Database?cited by 0
  12. 2025GeoGrid-Bench: Can Foundation Models Understand Multimodal Gridded Geo-Spatial Data?cited by 0
  13. 2026Accurate Table Question Answering with Accessible LLMscited by 0
  14. 2026How Do Language Models Understand Tables? A Mechanistic Analysis of Cell Locationcited by 0
  15. 2026V-tableR1: Process-Supervised Multimodal Table Reasoning with Critic-Guided Policy Optimizationcited by 0
  16. 2026Efficient Table QA via TableGrid Navigation and Progressive Inference Promptingcited by 0
  17. 2026Practical Quantum CIM Empowerment via All-Domestic-Core Agentic Large Modelcited by 0

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  1. 2026ProgramTab: Boosting Table Reasoning of LLMs via Programmatic Paradigm
  2. 2024Tree-of-Table: Unleashing the Power of LLMs for Enhanced Large-Scale Table Understanding
  3. 2024Tables as Texts or Images: Evaluating the Table Reasoning Ability of LLMs and MLLMs
  4. 2025Improving Table Understanding with LLMs and Entity-Oriented Search
  5. 2025TableReasoner: Advancing Table Reasoning Framework with Large Language Models
  6. 2024TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning
  7. 2024TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition
  8. 2024Large Language Model for Table Processing: A Survey