mlsanityData to 14 Oct 2026

Natural Language Interfaces for Tabular Data Querying and Visualization: A Survey

arXiv 2310.17894 ↗First posted 27 Oct 2023cs.CL cs.AIcited by 27

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Abstract (arXiv)

The emergence of natural language processing has revolutionized the way users interact with tabular data, enabling a shift from traditional query languages and manual plotting to more intuitive, language-based interfaces. The rise of large language models (LLMs) such as ChatGPT and its successors has further advanced this field, opening new avenues for natural language processing techniques. This survey presents a comprehensive overview of natural language interfaces for tabular data querying and visualization, which allow users to interact with data using natural language queries. We introduce the fundamental concepts and techniques underlying these interfaces with a particular emphasis on semantic parsing, the key technology facilitating the translation from natural language to SQL queries or data visualization commands. We then delve into the recent advancements in Text-to-SQL and Text-to-Vis problems from the perspectives of datasets, methodologies, metrics, and system designs. This includes a deep dive into the influence of LLMs, highlighting their strengths, limitations, and potential for future improvements. Through this survey, we aim to provide a roadmap for researchers and practitioners interested in developing and applying natural language interfaces for data interaction in the era of large language models.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). Builds on 94 of its 146 references that are in the map. First posted on arXiv 27 Oct 2023.

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94 of 146 references.

References · 94

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38 more
  1. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 477
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  15. 2018Improving Text-to-SQL Evaluation Methodologycited by 135
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Citing papers per year: 2024: 11; 2025: 10; 2026: 6.

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  1. 2024Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Surveycited by 159
  2. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 120
  3. 2024A Survey on Employing Large Language Models for Text-to-SQL Taskscited by 67
  4. 2024The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Modelscited by 67
  5. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 56
  6. 2024VisEval: A Benchmark for Data Visualization in the Era of Large Language Modelscited by 45
  7. 2025Advancing Tool-Augmented Large Language Models via Meta-Verification and Reflection Learningcited by 24
  8. 2024PoTable: Towards Systematic Thinking via Plan-then-Execute Stage Reasoning on Tablescited by 14
  9. 2025ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQLcited by 8
  10. 2024Synthetic SQL Column Descriptions and Their Impact on Text-to-SQL Performancecited by 6
  11. 2024Towards Optimizing SQL Generation via LLM Routingcited by 5
  12. 2026MultiVis-Agent: A Multi-Agent Framework with Logic Rules for Reliable and Comprehensive Cross-Modal Data Visualizationcited by 3
15 more
  1. 2024DataVisT5: A Pre-trained Language Model for Jointly Understanding Text and Data Visualizationcited by 2
  2. 2024Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizationscited by 2
  3. 2025LLM Empowered Prototype Learning for Zero and Few-Shot Tasks on Tabular Datacited by 2
  4. 2025Beyond Query-Level Comparison: Fine-Grained Reinforcement Learning for Text-to-SQL with Automated Interpretable Critiquescited by 2
  5. 2025ClimateSOM: A Visual Analysis Workflow for Climate Ensemble Datasetscited by 1
  6. 2025Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoningcited by 1
  7. 2026MATA: Multi-Agent Framework for Reliable and Flexible Table Question Answeringcited by 1
  8. 2026Every Step Counts: Step-Level Credit Assignment for Tool-Integrated Text-to-SQLcited by 1
  9. 2026TwinBI: An Agentic Digital Twin for Efficient Augmented Interactions with Business Intelligence Dashboardscited by 1
  10. 2026SQLMorph: Query Mutation and Fine-Grained Metrics for Text-to-SQL Evaluationcited by 1
  11. 2025Enhancing Omics Cohort Discovery for Research on Neurodegeneration through Ontology-Augmented Embedding Modelscited by 0
  12. 2025A Multimodal Conversational Agent for Tabular Data Analysiscited by 0
  13. 2025OsmT: Bridging OpenStreetMap Queries and Natural Language with Open-source Tag-aware Language Modelscited by 0
  14. 2025NOVAID: Natural-language Observability Visualization Assistant for ITOps Dashboard Widget Generationcited by 0
  15. 2026Natural Language Interfaces for Spatial and Temporal Databases: A Comprehensive Overview of Methods, Taxonomy, and Future Directionscited by 0