mlsanityData to 7 Oct 2026

Overview of the TREC 2019 deep learning track

arXiv 2003.07820 ↗First posted 17 Mar 2020cs.IR cs.CL cs.LGcited by 282

Not on the map. Why?

Cited by 34 in Retrieval-augmented generation, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The Deep Learning Track is a new track for TREC 2019, with the goal of studying ad hoc ranking in a large data regime. It is the first track with large human-labeled training sets, introducing two sets corresponding to two tasks, each with rigorous TREC-style blind evaluation and reusable test sets. The document retrieval task has a corpus of 3.2 million documents with 367 thousand training queries, for which we generate a reusable test set of 43 queries. The passage retrieval task has a corpus of 8.8 million passages with 503 thousand training queries, for which we generate a reusable test set of 43 queries. This year 15 groups submitted a total of 75 runs, using various combinations of deep learning, transfer learning and traditional IR ranking methods. Deep learning runs significantly outperformed traditional IR runs. Possible explanations for this result are that we introduced large training data and we included deep models trained on such data in our judging pools, whereas some past studies did not have such training data or pooling.

Key facts. Cited by 282 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Mar 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 22; 2022: 37; 2023: 37; 2024: 55; 2025: 80; 2026: 51.

282 papers.

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  1. 2022Precise Zero-Shot Dense Retrieval without Relevance Labelscited by 508
  2. 2024BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrievalcited by 153
  3. 2023Query2doc: Query Expansion with Large Language Modelscited by 146
  4. 2021SPLADE v2: Sparse Lexical and Expansion Model for Information Retrievalcited by 126
  5. 2024HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughlycited by 119
  6. 2021Mr. TyDi: A Multi-lingual Benchmark for Dense Retrievalcited by 118
  7. 2021mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Datasetcited by 116
  8. 2023How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrievalcited by 116
  9. 2021COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted Listcited by 113
  10. 2022From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effectivecited by 98
  11. 2025On the Theoretical Limitations of Embedding-Based Retrievalcited by 98
  12. 2024From Matching to Generation: A Survey on Generative Information Retrievalcited by 89
38 more
  1. 2024Searching for Best Practices in Retrieval-Augmented Generationcited by 83
  2. 2023Zero-Shot Listwise Document Reranking with a Large Language Modelcited by 81
  3. 2023RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Modelscited by 69
  4. 2025Rank1: Test-Time Compute for Reranking in Information Retrievalcited by 68
  5. 2023SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrievalcited by 61
  6. 2025Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learningcited by 58
  7. 2023A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Modelscited by 53
  8. 2023How Does Generative Retrieval Scale to Millions of Passages?cited by 47
  9. 2024TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategycited by 47
  10. 2021Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedbackcited by 45
  11. 2024Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankerscited by 42
  12. 2021A Statutory Article Retrieval Dataset in Frenchcited by 40
  13. 2024Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Modelscited by 39
  14. 2022Curriculum Learning for Dense Retrieval Distillationcited by 38
  15. 2022Towards Robust Ranker for Text Retrievalcited by 37
  16. 2022Order-Disorder: Imitation Adversarial Attacks for Black-box Neural Ranking Modelscited by 37
  17. 2021Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankerscited by 34
  18. 2024INQUIRE: A Natural World Text-to-Image Retrieval Benchmarkcited by 33
  19. 2023QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operationscited by 30
  20. 2023Found in the Middle: Permutation Self-Consistency Improves Listwise Ranking in Large Language Modelscited by 30
  21. 2022Fine-Grained Distillation for Long Document Retrievalcited by 29
  22. 2025Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Surveycited by 29
  23. 2021Extreme Multi-label Learning for Semantic Matching in Product Searchcited by 28
  24. 2024APEER: Automatic Prompt Engineering Enhances Large Language Model Rerankingcited by 28
  25. 2025One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systemscited by 28
  26. 2025Rank-K: Test-Time Reasoning for Listwise Rerankingcited by 28
  27. 2021Simplified Data Wrangling with ir_datasetscited by 27
  28. 2021B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc Retrievalcited by 25
  29. 2023Large Language Models are Strong Zero-Shot Retrievercited by 25
  30. 2023When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasetscited by 25
  31. 2025Provence: efficient and robust context pruning for retrieval-augmented generationcited by 25
  32. 2025REARANK: Reasoning Re-ranking Agent via Reinforcement Learningcited by 24
  33. 2022CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typoscited by 22
  34. 2025Overview of the TREC 2022 deep learning trackcited by 22
  35. 2022Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reductioncited by 21
  36. 2022PROD: Progressive Distillation for Dense Retrievalcited by 20
  37. 2023Language Models As Semantic Indexerscited by 20
  38. 2024Ranked List Truncation for Large Language Model-based Re-Rankingcited by 20

50 most cited of 282 All 282 (JSON)