Web Table Extraction, Retrieval and Augmentation: A Survey
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Abstract (arXiv)
Tables are a powerful and popular tool for organizing and manipulating data. A vast number of tables can be found on the Web, which represents a valuable knowledge resource. The objective of this survey is to synthesize and present two decades of research on web tables. In particular, we organize existing literature into six main categories of information access tasks: table extraction, table interpretation, table search, question answering, knowledge base augmentation, and table augmentation. For each of these tasks, we identify and describe seminal approaches, present relevant resources, and point out interdependencies among the different tasks.
Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Feb 2020.
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Citing papers per year: 2021: 5; 2022: 3; 2023: 1; 2024: 2; 2025: 2; 2026: 2.
15 papers.
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- 2021TCN: Table Convolutional Network for Web Table Interpretationcited by 24
- 2025Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End Systemcited by 23
- 2024Tabular Data Augmentation for Machine Learning: Progress and Prospects of Embracing Generative AIcited by 15
- 2021Towards Neural Schema Alignment for OpenStreetMap and Knowledge Graphscited by 5
- 2026Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pretrainingcited by 4
- 2022Enhancing Tabular Reasoning with Pattern Exploiting Trainingcited by 3
- 2023Tab2KG: Semantic Table Interpretation with Lightweight Semantic Profilescited by 2
- 2021Table Caption Generation in Scholarly Documents Leveraging Pre-trained Language Modelscited by 1
- 2022Rows from Many Sources: Enriching row completions from Wikidata with a pre-trained Language Modelcited by 1
- 2024TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakescited by 1
- 2021Type Prediction Systemscited by 0
- 2021Relation Extraction from Tables using Artificially Generated Metadatacited by 0
- 2026FollowTable: A Benchmark for Instruction-Following Table Retrieval1 May 2026
- 2026Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pretraining23 Feb 2026
- 2025Conceptual Schema Inference for Tabular Datasets using Large Language Models4 Sep 2025
- 2025Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End System12 Apr 2025
- 2024Tabular Data Augmentation for Machine Learning: Progress and Prospects of Embracing Generative AI31 Jul 2024
- 2024TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes28 Jun 2024
- 2023Tab2KG: Semantic Table Interpretation with Lightweight Semantic Profiles2 Feb 2023
- 2022Enhancing Tabular Reasoning with Pattern Exploiting Training21 Oct 2022
- 2022Russian Web Tables: A Public Corpus of Web Tables for Russian Language Based on Wikipedia3 Oct 2022
- 2022Rows from Many Sources: Enriching row completions from Wikidata with a pre-trained Language Model14 Apr 2022
- 2021Relation Extraction from Tables using Artificially Generated Metadata24 Aug 2021
- 2021Table Caption Generation in Scholarly Documents Leveraging Pre-trained Language Models18 Aug 2021
3 more
- 2021Towards Neural Schema Alignment for OpenStreetMap and Knowledge Graphs28 Jul 2021
- 2021Type Prediction Systems2 Apr 2021
- 2021TCN: Table Convolutional Network for Web Table Interpretation17 Feb 2021
- 2021TCN: Table Convolutional Network for Web Table Interpretationcited by 24
- 2024Tabular Data Augmentation for Machine Learning: Progress and Prospects of Embracing Generative AIcited by 15
- 2021Towards Neural Schema Alignment for OpenStreetMap and Knowledge Graphscited by 5
- 2023Tab2KG: Semantic Table Interpretation with Lightweight Semantic Profilescited by 2
- 2021Table Caption Generation in Scholarly Documents Leveraging Pre-trained Language Modelscited by 1
- 2022Rows from Many Sources: Enriching row completions from Wikidata with a pre-trained Language Modelcited by 1
- 2024TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakescited by 1
- 2021Type Prediction Systemscited by 0
- 2021Relation Extraction from Tables using Artificially Generated Metadatacited by 0
- 2022Russian Web Tables: A Public Corpus of Web Tables for Russian Language Based on Wikipediacited by 0
- 2025Conceptual Schema Inference for Tabular Datasets using Large Language Modelscited by 0
- 2026FollowTable: A Benchmark for Instruction-Following Table Retrievalcited by 0
- 2026FollowTable: A Benchmark for Instruction-Following Table Retrieval1 May 2026
- 2025Conceptual Schema Inference for Tabular Datasets using Large Language Models4 Sep 2025
- 2024Tabular Data Augmentation for Machine Learning: Progress and Prospects of Embracing Generative AI31 Jul 2024
- 2024TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes28 Jun 2024
- 2023Tab2KG: Semantic Table Interpretation with Lightweight Semantic Profiles2 Feb 2023
- 2022Russian Web Tables: A Public Corpus of Web Tables for Russian Language Based on Wikipedia3 Oct 2022
- 2022Rows from Many Sources: Enriching row completions from Wikidata with a pre-trained Language Model14 Apr 2022
- 2021Relation Extraction from Tables using Artificially Generated Metadata24 Aug 2021
- 2021Table Caption Generation in Scholarly Documents Leveraging Pre-trained Language Models18 Aug 2021
- 2021Towards Neural Schema Alignment for OpenStreetMap and Knowledge Graphs28 Jul 2021
- 2021Type Prediction Systems2 Apr 2021
- 2021TCN: Table Convolutional Network for Web Table Interpretation17 Feb 2021