mlsanityData to 7 Oct 2026

Reading Wikipedia to Answer Open-Domain Questions

arXiv 1704.00051 ↗First posted 31 Mar 2017cs.CLcited by 777

Not on the map. Why?

Cited by 139 in Retrieval-augmented generation, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article. This task of machine reading at scale combines the challenges of document retrieval (finding the relevant articles) with that of machine comprehension of text (identifying the answer spans from those articles). Our approach combines a search component based on bigram hashing and TF-IDF matching with a multi-layer recurrent neural network model trained to detect answers in Wikipedia paragraphs. Our experiments on multiple existing QA datasets indicate that (1) both modules are highly competitive with respect to existing counterparts and (2) multitask learning using distant supervision on their combination is an effective complete system on this challenging task.

Key facts. Cited by 777 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Mar 2017.

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Citing papers per year: 2020: 2; 2021: 163; 2022: 148; 2023: 162; 2024: 164; 2025: 91; 2026: 47.

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  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  2. 2023A Survey of Large Language Modelscited by 2,537
  3. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,126
  4. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,259
  5. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,225
  6. 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,210
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  9. 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 803
  10. 2022A-OKVQA: A Benchmark for Visual Question Answering using World Knowledgecited by 702
  11. 2023In-Context Retrieval-Augmented Language Modelscited by 694
  12. 2021Retrieval Augmentation Reduces Hallucination in Conversationcited by 691
38 more
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  4. 2023Active Retrieval Augmented Generationcited by 506
  5. 2021Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Surveycited by 457
  6. 2024A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Modelscited by 450
  7. 2022Memory-Based Model Editing at Scalecited by 443
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  9. 2023Cognitive Architectures for Language Agentscited by 422
  10. 2023Augmented Language Models: a Surveycited by 398
  11. 2023Editing Large Language Models: Problems, Methods, and Opportunitiescited by 367
  12. 2023Making Retrieval-Augmented Language Models Robust to Irrelevant Contextcited by 364
  13. 2021Entity-Based Knowledge Conflicts in Question Answeringcited by 349
  14. 2022Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLPcited by 316
  15. 2022Generate rather than Retrieve: Large Language Models are Strong Context Generatorscited by 296
  16. 2022RARR: Researching and Revising What Language Models Say, Using Language Modelscited by 286
  17. 2021Beyond Goldfish Memory: Long-Term Open-Domain Conversationcited by 266
  18. 2023FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarioscited by 247
  19. 2022RealTime QA: What's the Answer Right Now?cited by 239
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  24. 2021PAQ: 65 Million Probably-Asked Questions and What You Can Do With Themcited by 198
  25. 2023Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Modelscited by 180
  26. 2021Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answeringcited by 178
  27. 2021FeTaQA: Free-form Table Question Answeringcited by 174
  28. 2021FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured informationcited by 166
  29. 2024FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Researchcited by 165
  30. 2022Improving Passage Retrieval with Zero-Shot Question Generationcited by 164
  31. 2024BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrievalcited by 153
  32. 2021A Dataset for Answering Time-Sensitive Questionscited by 150
  33. 2023Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answeringcited by 150
  34. 2023Knowledge Graph Prompting for Multi-Document Question Answeringcited by 150
  35. 2023Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentationcited by 146
  36. 2021SituatedQA: Incorporating Extra-Linguistic Contexts into QAcited by 145
  37. 2022Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidencecited by 142
  38. 2021Simple Entity-Centric Questions Challenge Dense Retrieverscited by 140

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