mlsanityData to 7 Oct 2026

Large Language Model for Table Processing: A Survey

arXiv 2402.05121 ↗First posted 4 Feb 2024cs.AI cs.CLcited by 52

Not on the map. Why?

Abstract (arXiv)

Tables, typically two-dimensional and structured to store large amounts of data, are essential in daily activities like database queries, spreadsheet manipulations, web table question answering, and image table information extraction. Automating these table-centric tasks with Large Language Models (LLMs) or Visual Language Models (VLMs) offers significant public benefits, garnering interest from academia and industry. This survey provides a comprehensive overview of table-related tasks, examining both user scenarios and technical aspects. It covers traditional tasks like table question answering as well as emerging fields such as spreadsheet manipulation and table data analysis. We summarize the training techniques for LLMs and VLMs tailored for table processing. Additionally, we discuss prompt engineering, particularly the use of LLM-powered agents, for various table-related tasks. Finally, we highlight several challenges, including diverse user input when serving and slow thinking using chain-of-thought.

Key facts. Cited by 52 papers in the map (data through 7 Oct 2026). Builds on 78 of its 135 references that are in the map. First posted on arXiv 4 Feb 2024.

Builds on

78 of 135 references.

References · 78

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
  4. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  6. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  7. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  8. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  9. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  10. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  11. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  12. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,767
38 more
  1. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  2. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  3. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,769
  4. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  5. 2021Program Synthesis with Large Language Modelscited by 3,509
  6. 2023A Survey of Large Language Modelscited by 2,537
  7. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  8. 2023Code Llama: Open Foundation Models for Codecited by 2,105
  9. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  10. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Modelscited by 1,397
  11. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  12. 2023StarCoder: may the source be with you!cited by 790
  13. 2023WizardCoder: Empowering Code Large Language Models with Evol-Instructcited by 728
  14. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 679
  15. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
  16. 2019LayoutLM: Pre-training of Text and Layout for Document Image Understandingcited by 549
  17. 2015Compositional Semantic Parsing on Semi-Structured Tablescited by 509
  18. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  19. 2022DS-1000: A Natural and Reliable Benchmark for Data Science Code Generationcited by 442
  20. 2020TAPAS: Weakly Supervised Table Parsing via Pre-trainingcited by 432
  21. 2019TabFact: A Large-scale Dataset for Table-based Fact Verificationcited by 425
  22. 2020LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understandingcited by 406
  23. 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 395
  24. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  25. 2023StructGPT: A General Framework for Large Language Model to Reason over Structured Datacited by 339
  26. 2020ToTTo: A Controlled Table-To-Text Generation Datasetcited by 267
  27. 2020HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Datacited by 263
  28. 2023Magicoder: Empowering Code Generation with OSS-Instructcited by 251
  29. 2019Image-based table recognition: data, model, and evaluationcited by 233
  30. 2021TAPEX: Table Pre-training via Learning a Neural SQL Executorcited by 233
  31. 2022Binding Language Models in Symbolic Languagescited by 224
  32. 2022Grounded Copilot: How Programmers Interact with Code-Generating Modelscited by 216
  33. 2019A Theoretical Analysis of Deep Q-Learningcited by 212
  34. 2023RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLcited by 191
  35. 2024Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understandingcited by 185
  36. 2023Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoningcited by 177
  37. 2021FeTaQA: Free-form Table Question Answeringcited by 174
  38. 2020DART: Open-Domain Structured Data Record to Text Generationcited by 144

50 most cited of 78 All 78 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 14; 2025: 30; 2026: 8.

52 papers.

Sort:

By area:

  1. 2024CodeS: Towards Building Open-source Language Models for Text-to-SQLcited by 183
  2. 2024TableBench: A Comprehensive and Complex Benchmark for Table Question Answeringcited by 127
  3. 2024LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputationcited by 25
  4. 2025TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoningcited by 22
  5. 2025nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflowcited by 21
  6. 2024Transforming Wearable Data into Personal Health Insights using Large Language Model Agentscited by 19
  7. 2024PoTable: Towards Systematic Thinking via Plan-then-Execute Stage Reasoning on Tablescited by 13
  8. 2024Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representationscited by 12
  9. 2024AutoPrep: Natural Language Question-Aware Data Preparation with a Multi-Agent Frameworkcited by 12
  10. 2024MiMoTable: A Multi-scale Spreadsheet Benchmark with Meta Operations for Table Reasoningcited by 12
  11. 2024SPAGHETTI: Open-Domain Question Answering from Heterogeneous Data Sources with Retrieval and Semantic Parsingcited by 11
  12. 2025RoT: Enhancing Table Reasoning with Iterative Row-Wise Traversalscited by 10
38 more
  1. 2025Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challengescited by 10
  2. 2024ALTER: Augmentation for Large-Table-Based Reasoningcited by 9
  3. 2024Matchmaker: Self-Improving Large Language Model Programs for Schema Matchingcited by 9
  4. 2024Large Language Models Engineer Too Many Simple Features For Tabular Datacited by 8
  5. 2025NeedleInATable: Exploring Long-Context Capability of Large Language Models towards Long-Structured Tablescited by 8
  6. 2025Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Modelscited by 7
  7. 2026SpreadsheetBench 2: Evaluating Agents on End-to-End Business Spreadsheet Workflowscited by 7
  8. 2025T2R-bench: A Benchmark for Generating Article-Level Reports from Real World Industrial Tablescited by 5
  9. 2026FinRule-Bench: A Benchmark for Joint Reasoning over Financial Tables and Principlescited by 5
  10. 2025TableDreamer: Progressive and Weakness-guided Data Synthesis from Scratch for Table Instruction Tuningcited by 4
  11. 2025Chain-of-Query: Unleashing the Power of LLMs in SQL-Aided Table Understanding via Multi-Agent Collaborationcited by 4
  12. 2025Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluationcited by 4
  13. 2026Hunt Instead of Wait: Evaluating Deep Data Research on Large Language Modelscited by 4
  14. 2024Using Large Language Models to Generate Clinical Trial Tables and Figurescited by 3
  15. 2025JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMscited by 3
  16. 2025MDBench: A Synthetic Multi-Document Reasoning Benchmark Generated with Knowledge Guidancecited by 3
  17. 2025TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Modelscited by 3
  18. 2025Empowering Tabular Data Preparation with Language Models: Why and How?cited by 3
  19. 2025Information Extraction From Fiscal Documents Using LLMscited by 3
  20. 2025Structural Deep Encoding for Table Question Answeringcited by 2
  21. 2025MOAT: Evaluating LMMs for Capability Integration and Instruction Groundingcited by 2
  22. 2025TabNSA: Native Sparse Attention for Efficient Tabular Data Learningcited by 2
  23. 2025LLM Inference Enhanced by External Knowledge: A Surveycited by 2
  24. 2025Toward Real-World Table Agents: Capabilities, Workflows, and Design Principles for LLM-based Table Intelligencecited by 2
  25. 2024Towards More Effective Table-to-Text Generation: Assessing In-Context Learning and Self-Evaluation with Open-Source Modelscited by 1
  26. 2025LLM driven Text-to-Table Generation through Sub-Tasks Guidance and Iterative Refinementcited by 1
  27. 2025SODBench: A Large Language Model Approach to Documenting Spreadsheet Operationscited by 1
  28. 2025iLTM: Integrated Large Tabular Modelcited by 1
  29. 2025Error-Driven Prompt Optimization for Arithmetic Reasoningcited by 1
  30. 2026ReasonTabQA: A Comprehensive Benchmark for Table Question Answering from Real World Industrial Scenarioscited by 1
  31. 2026Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Modelscited by 1
  32. 2025Towards Large Language Models for Lunar Mission Planning and In Situ Resource Utilizationcited by 0
  33. 2025FoGE: Fock Space inspired encoding for graph promptingcited by 0
  34. 2025Innovative tokenisation of structured data for LLM trainingcited by 0
  35. 2025Large Language Models as Universal Predictors? An Empirical Study on Small Tabular Datasetscited by 0
  36. 2025Summarize-Exemplify-Reflect: Data-driven Insight Distillation Empowers LLMs for Few-shot Tabular Classificationcited by 0
  37. 2025SQuARE: Structured Query & Adaptive Retrieval Engine For Tabular Formatscited by 0
  38. 2026DataFactory: Collaborative Multi-Agent Framework for Advanced Table Question Answeringcited by 0

50 most cited of 52 All 52 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2024A Survey of Table Reasoning with Large Language Models
  2. 2024Tables as Texts or Images: Evaluating the Table Reasoning Ability of LLMs and MLLMs
  3. 2024TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
  4. 2025Enhancing Large Vision-Language Models with Layout Modality for Table Question Answering on Japanese Annual Securities Reports
  5. 2025Agentic LLMs for Question Answering over Tabular Data
  6. 2026Efficient Table Retrieval and Understanding with Multimodal Large Language Models
  7. 2026TABVERSE: Benchmarking Cross-Format Table Understanding in LLMs and VLMs
  8. 2025Texts or Images? A Fine-grained Analysis on the Effectiveness of Input Representations and Models for Table Question Answering