mlsanityData to 7 Oct 2026

Wizard of Wikipedia: Knowledge-Powered Conversational agents

arXiv 1811.01241 ↗First posted 3 Nov 2018cs.CLcited by 530

Not on the map. Why?

Cited by 68 in Retrieval-augmented generation, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In open-domain dialogue intelligent agents should exhibit the use of knowledge, however there are few convincing demonstrations of this to date. The most popular sequence to sequence models typically "generate and hope" generic utterances that can be memorized in the weights of the model when mapping from input utterance(s) to output, rather than employing recalled knowledge as context. Use of knowledge has so far proved difficult, in part because of the lack of a supervised learning benchmark task which exhibits knowledgeable open dialogue with clear grounding. To that end we collect and release a large dataset with conversations directly grounded with knowledge retrieved from Wikipedia. We then design architectures capable of retrieving knowledge, reading and conditioning on it, and finally generating natural responses. Our best performing dialogue models are able to conduct knowledgeable discussions on open-domain topics as evaluated by automatic metrics and human evaluations, while our new benchmark allows for measuring further improvements in this important research direction.

Key facts. Cited by 530 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Nov 2018.

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Citing papers per year: 2020: 1; 2021: 108; 2022: 138; 2023: 128; 2024: 88; 2025: 50; 2026: 17.

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  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  2. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,464
  3. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  4. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  5. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,800
  6. 2022LaMDA: Language Models for Dialog Applicationscited by 1,218
  7. 2022Atlas: Few-shot Learning with Retrieval Augmented Language Modelscited by 940
  8. 2022Galactica: A Large Language Model for Sciencecited by 736
  9. 2021Retrieval Augmentation Reduces Hallucination in Conversationcited by 691
  10. 2023The Internal State of an LLM Knows When It's Lyingcited by 644
  11. 2023A Comprehensive Overview of Large Language Modelscited by 639
  12. 2025BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agentscited by 616
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  1. 2023Active Retrieval Augmented Generationcited by 506
  2. 2022Knowledge Unlearning for Mitigating Privacy Risks in Language Modelscited by 424
  3. 2023Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedbackcited by 351
  4. 2022One Embedder, Any Task: Instruction-Finetuned Text Embeddingscited by 329
  5. 2022Generate rather than Retrieve: Large Language Models are Strong Context Generatorscited by 296
  6. 2021Beyond Goldfish Memory: Long-Term Open-Domain Conversationcited by 266
  7. 2022Towards a Unified Multi-Dimensional Evaluator for Text Generationcited by 264
  8. 2023ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systemscited by 259
  9. 2021Measuring Attribution in Natural Language Generation Modelscited by 253
  10. 2025Agentic Retrieval-Augmented Generation: A Survey on Agentic RAGcited by 242
  11. 2021The GEM Benchmark: Natural Language Generation, its Evaluation and Metricscited by 239
  12. 2022OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalizationcited by 235
  13. 2023Woodpecker: Hallucination Correction for Multimodal Large Language Modelscited by 223
  14. 2021Internet-Augmented Dialogue Generationcited by 217
  15. 2024From Persona to Personalization: A Survey on Role-Playing Language Agentscited by 206
  16. 2023Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificitycited by 204
  17. 2022BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagecited by 197
  18. 2023RA-DIT: Retrieval-Augmented Dual Instruction Tuningcited by 194
  19. 2021DialogSum: A Real-Life Scenario Dialogue Summarization Datasetcited by 181
  20. 2021Towards Continual Knowledge Learning of Language Modelscited by 172
  21. 2021Hurdles to Progress in Long-form Question Answeringcited by 166
  22. 2022SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualizationcited by 166
  23. 2024FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Researchcited by 165
  24. 2021ExT5: Towards Extreme Multi-Task Scaling for Transfer Learningcited by 161
  25. 2022"I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Datasetcited by 160
  26. 2022A Survey on Retrieval-Augmented Text Generationcited by 157
  27. 2024Evaluation of Retrieval-Augmented Generation: A Surveycited by 146
  28. 2021CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLPcited by 142
  29. 2024A Human-Inspired Reading Agent with Gist Memory of Very Long Contextscited by 140
  30. 2022On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?cited by 137
  31. 2021Q2: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answeringcited by 131
  32. 2023Walking Down the Memory Maze: Beyond Context Limit through Interactive Readingcited by 129
  33. 2022A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Modelscited by 128
  34. 2023MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problemscited by 128
  35. 2023Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigationcited by 123
  36. 2022TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Modelscited by 117
  37. 2024RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systemscited by 115
  38. 2022Autoregressive Search Engines: Generating Substrings as Document Identifierscited by 112

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