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Open Domain Question Answering over Tables via Dense Retrieval

arXiv 2103.12011 ↗First posted 22 Mar 2021cs.CLcited by 74

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Abstract (arXiv)

Recent advances in open-domain QA have led to strong models based on dense retrieval, but only focused on retrieving textual passages. In this work, we tackle open-domain QA over tables for the first time, and show that retrieval can be improved by a retriever designed to handle tabular context. We present an effective pre-training procedure for our retriever and improve retrieval quality with mined hard negatives. As relevant datasets are missing, we extract a subset of Natural Questions (Kwiatkowski et al., 2019) into a Table QA dataset. We find that our retriever improves retrieval results from 72.0 to 81.1 recall@10 and end-to-end QA results from 33.8 to 37.7 exact match, over a BERT based retriever.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). Builds on 19 of its 25 references that are in the map. First posted on arXiv 22 Mar 2021.

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19 of 25 references.

References · 19

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  3. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  4. 2017Billion-scale similarity search with GPUscited by 2,477
  5. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,126
  6. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  7. 2020Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrievalcited by 846
  8. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  9. 2019Latent Retrieval for Weakly Supervised Open Domain Question Answeringcited by 691
  10. 2020TAPAS: Weakly Supervised Table Parsing via Pre-trainingcited by 432
  11. 2017Efficient Natural Language Response Suggestion for Smart Replycited by 228
  12. 2018Open Domain Question Answering Using Early Fusion of Knowledge Bases and Textcited by 167
7 more
  1. 2020Open Question Answering over Tables and Textcited by 163
  2. 2019End-to-End Open-Domain Question Answering with BERTserinicited by 152
  3. 2019Learning Dense Representations for Entity Retrievalcited by 122
  4. 2020Understanding tables with intermediate pre-trainingcited by 68
  5. 2015Neural Programmer: Inducing Latent Programs with Gradient Descentcited by 32
  6. 2021Representations for Question Answering from Documents with Tables and Textcited by 21
  7. 2016Learning Recurrent Span Representations for Extractive Question Answeringcited by 14

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Citing papers per year: 2021: 6; 2022: 10; 2023: 16; 2024: 14; 2025: 14; 2026: 14.

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  1. 2024Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Surveycited by 157
  2. 2021MATE: Multi-view Attention for Table Transformer Efficiencycited by 54
  3. 2021AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industrycited by 44
  4. 2022A Survey on Table Question Answering: Recent Advancescited by 41
  5. 2023Open-WikiTable: Dataset for Open Domain Question Answering with Complex Reasoning over Tablecited by 40
  6. 2023Augmented Large Language Models with Parametric Knowledge Guidingcited by 37
  7. 2023HYTREL: Hypergraph-enhanced Tabular Data Representation Learningcited by 35
  8. 2024Text2SQL is Not Enough: Unifying AI and Databases with TAGcited by 34
  9. 2021Open Domain Question Answering with A Unified Knowledge Interfacecited by 32
  10. 2022OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answeringcited by 29
  11. 2022Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbationcited by 28
  12. 2024Is Table Retrieval a Solved Problem? Exploring Join-Aware Multi-Table Retrievalcited by 27
38 more
  1. 2024OpenTab: Advancing Large Language Models as Open-domain Table Reasonerscited by 25
  2. 2021ReasonBERT: Pre-trained to Reason with Distant Supervisioncited by 22
  3. 2025Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End Systemcited by 22
  4. 2023Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learningcited by 20
  5. 2022Mixed-modality Representation Learning and Pre-training for Joint Table-and-Text Retrieval in OpenQAcited by 17
  6. 2025RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarkingcited by 17
  7. 2025TARGET: Benchmarking Table Retrieval for Generative Taskscited by 17
  8. 2025Table Foundation Models: on knowledge pre-training for tabular learningcited by 15
  9. 2022End-to-End Table Question Answering via Retrieval-Augmented Generationcited by 12
  10. 2021Multi-modal Retrieval of Tables and Texts Using Tri-encoder Modelscited by 11
  11. 2022Parameter-Efficient Abstractive Question Answering over Tables or Textcited by 11
  12. 2022Table Retrieval May Not Necessitate Table-specific Model Designcited by 11
  13. 2024SPAGHETTI: Open-Domain Question Answering from Heterogeneous Data Sources with Retrieval and Semantic Parsingcited by 11
  14. 2022ReSel: N-ary Relation Extraction from Scientific Text and Tables by Learning to Retrieve and Selectcited by 10
  15. 2022DyRRen: A Dynamic Retriever-Reranker-Generator Model for Numerical Reasoning over Tabular and Textual Datacited by 10
  16. 2024cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Paperscited by 10
  17. 2024SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQAcited by 9
  18. 2025WikiMixQA: A Multimodal Benchmark for Question Answering over Tables and Chartscited by 8
  19. 2023cTBLS: Augmenting Large Language Models with Conversational Tablescited by 7
  20. 2025Granite Embedding R2 Modelscited by 7
  21. 2023The StatCan Dialogue Dataset: Retrieving Data Tables through Conversations with Genuine Intentscited by 6
  22. 2023Localize, Retrieve and Fuse: A Generalized Framework for Free-Form Question Answering over Tablescited by 6
  23. 2024TANQ: An open domain dataset of table answered questionscited by 6
  24. 2024Unified Multimodal Interleaved Document Representation for Retrievalcited by 6
  25. 2023Bridge the Gap between Language models and Tabular Understandingcited by 5
  26. 2024Database-Augmented Query Representation for Information Retrievalcited by 5
  27. 2024UniHGKR: Unified Instruction-aware Heterogeneous Knowledge Retrieverscited by 5
  28. 2023AdaTyper: Adaptive Semantic Column Type Detectioncited by 4
  29. 2025RASL: Retrieval Augmented Schema Linking for Massive Database Text-to-SQLcited by 4
  30. 2022Improving Cross-task Generalization of Unified Table-to-text Models with Compositional Task Configurationscited by 3
  31. 2023Retrieval-Based Transformer for Table Augmentationcited by 3
  32. 2023InfoSync: Information Synchronization across Multilingual Semi-structured Tablescited by 3
  33. 2024iTBLS: A Dataset of Interactive Conversations Over Tabular Informationcited by 3
  34. 2024Reasoning Factual Knowledge in Structured Data with Large Language Modelscited by 3
  35. 2024Multi-Field Adaptive Retrievalcited by 3
  36. 2025Empowering Tabular Data Preparation with Language Models: Why and How?cited by 3
  37. 2025HyFedRAG: A Federated Retrieval-Augmented Generation Framework for Heterogeneous and Privacy-Sensitive Datacited by 3
  38. 2023Embeddings for Tabular Data: A Surveycited by 2

50 most cited of 74 All 74 (JSON)