mlsanityData to 7 Oct 2026

Document Expansion by Query Prediction

arXiv 1904.08375 ↗First posted 17 Apr 2019cs.IR cs.LGcited by 225

Not on the map. Why?

Cited by 28 in Retrieval-augmented generation, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

One technique to improve the retrieval effectiveness of a search engine is to expand documents with terms that are related or representative of the documents' content.From the perspective of a question answering system, this might comprise questions the document can potentially answer. Following this observation, we propose a simple method that predicts which queries will be issued for a given document and then expands it with those predictions with a vanilla sequence-to-sequence model, trained using datasets consisting of pairs of query and relevant documents. By combining our method with a highly-effective re-ranking component, we achieve the state of the art in two retrieval tasks. In a latency-critical regime, retrieval results alone (without re-ranking) approach the effectiveness of more computationally expensive neural re-rankers but are much faster.

Key facts. Cited by 225 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Apr 2019.

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Citing papers per year: 2021: 23; 2022: 34; 2023: 39; 2024: 32; 2025: 46; 2026: 51.

225 papers.

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  1. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,225
  2. 2023Cognitive Architectures for Language Agentscited by 422
  3. 2023Improving Text Embeddings with Large Language Modelscited by 295
  4. 2022Transformer Memory as a Differentiable Search Indexcited by 242
  5. 2021PAQ: 65 Million Probably-Asked Questions and What You Can Do With Themcited by 198
  6. 2021Overview of the TREC 2020 deep learning trackcited by 193
  7. 2021RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-rankingcited by 175
  8. 2023Query2doc: Query Expansion with Large Language Modelscited by 146
  9. 2023AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Webcited by 144
  10. 2021SPLADE v2: Sparse Lexical and Expansion Model for Information Retrievalcited by 126
  11. 2021GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrievalcited by 119
  12. 2022Autoregressive Search Engines: Generating Substrings as Document Identifierscited by 112
38 more
  1. 2022Task-aware Retrieval with Instructionscited by 107
  2. 2025Gemini Embedding: Generalizable Embeddings from Geminicited by 93
  3. 2021Adversarial Retriever-Ranker for dense text retrievalcited by 82
  4. 2021The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Modelscited by 81
  5. 2025Rank1: Test-Time Compute for Reranking in Information Retrievalcited by 68
  6. 2021PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrievalcited by 50
  7. 2024Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrievalcited by 50
  8. 2023How Does Generative Retrieval Scale to Millions of Passages?cited by 47
  9. 2021MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theoriescited by 46
  10. 2022ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder via Self On-the-fly Distillation for Dense Passage Retrievalcited by 41
  11. 2022GERE: Generative Evidence Retrieval for Fact Verificationcited by 38
  12. 2022Towards Robust Ranker for Text Retrievalcited by 37
  13. 2022What Are You Token About? Dense Retrieval as Distributions Over the Vocabularycited by 28
  14. 2024Scaling Laws For Dense Retrievalcited by 28
  15. 2022Multi-CPR: A Multi Domain Chinese Dataset for Passage Retrievalcited by 26
  16. 2022An Efficiency Study for SPLADE Modelscited by 26
  17. 2025Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generationcited by 26
  18. 2021B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc Retrievalcited by 25
  19. 2023When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasetscited by 25
  20. 2021Keyphrase Generation for Scientific Document Retrievalcited by 23
  21. 2021Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based QA Frameworkcited by 21
  22. 2022SimANS: Simple Ambiguous Negatives Sampling for Dense Text Retrievalcited by 21
  23. 2022QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillationcited by 21
  24. 2022In Defense of Cross-Encoders for Zero-Shot Retrievalcited by 21
  25. 2022PROD: Progressive Distillation for Dense Retrievalcited by 20
  26. 2024Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challengescited by 20
  27. 2022Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answeringcited by 19
  28. 2022UnifieR: A Unified Retriever for Large-Scale Retrievalcited by 19
  29. 2025NExtLong: Toward Effective Long-Context Training without Long Documentscited by 19
  30. 2023Large Search Model: Redefining Search Stack in the Era of LLMscited by 18
  31. 2023GAR-meets-RAG Paradigm for Zero-Shot Information Retrievalcited by 18
  32. 2022Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrievalcited by 17
  33. 2025FinDER: Financial Dataset for Question Answering and Evaluating Retrieval-Augmented Generationcited by 17
  34. 2022DuReader_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Enginecited by 15
  35. 2024Quest: Query-centric Data Synthesis Approach for Long-context Scaling of Large Language Modelcited by 15
  36. 2021Text-to-Text Multi-view Learning for Passage Re-rankingcited by 14
  37. 2023Context Aware Query Rewriting for Text Rankers using LLMcited by 14
  38. 2024OmniSearchSage: Multi-Task Multi-Entity Embeddings for Pinterest Searchcited by 13

50 most cited of 225 All 225 (JSON)