mlsanityData to 14 Oct 2026

Multi-Stage Document Ranking with BERT

arXiv 1910.14424 ↗First posted 31 Oct 2019cs.IR cs.LGcited by 201

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Cited by 31 in Retrieval-augmented generation, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The advent of deep neural networks pre-trained via language modeling tasks has spurred a number of successful applications in natural language processing. This work explores one such popular model, BERT, in the context of document ranking. We propose two variants, called monoBERT and duoBERT, that formulate the ranking problem as pointwise and pairwise classification, respectively. These two models are arranged in a multi-stage ranking architecture to form an end-to-end search system. One major advantage of this design is the ability to trade off quality against latency by controlling the admission of candidates into each pipeline stage, and by doing so, we are able to find operating points that offer a good balance between these two competing metrics. On two large-scale datasets, MS MARCO and TREC CAR, experiments show that our model produces results that are either at or comparable to the state of the art. Ablation studies show the contributions of each component and characterize the latency/quality tradeoff space.

Key facts. Cited by 201 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Oct 2019.

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Citing papers per year: 2021: 21; 2022: 28; 2023: 27; 2024: 52; 2025: 43; 2026: 30.

201 papers.

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  1. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,252
  2. 2022Text and Code Embeddings by Contrastive Pre-Trainingcited by 361
  3. 2023Large Language Models for Information Retrieval: A Surveycited by 331
  4. 2022SGPT: GPT Sentence Embeddings for Semantic Searchcited by 204
  5. 2021RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-rankingcited by 176
  6. 2021mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Datasetcited by 116
  7. 2022RankT5: Fine-Tuning T5 for Text Ranking with Ranking Lossescited by 115
  8. 2024Searching for Best Practices in Retrieval-Augmented Generationcited by 83
  9. 2023Zero-Shot Listwise Document Reranking with a Large Language Modelcited by 82
  10. 2021The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Modelscited by 81
  11. 2024A Survey on Retrieval-Augmented Text Generation for Large Language Modelscited by 77
  12. 2025Vision-Language Models Do Not Understand Negationcited by 72
38 more
  1. 2023RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Modelscited by 70
  2. 2024FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructionscited by 69
  3. 2023Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?cited by 54
  4. 2022Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generationcited by 48
  5. 2023How Does Generative Retrieval Scale to Millions of Passages?cited by 48
  6. 2023Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generatorscited by 43
  7. 2024Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankerscited by 43
  8. 2024VariErr NLI: Separating Annotation Error from Human Label Variationcited by 42
  9. 2022ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder via Self On-the-fly Distillation for Dense Passage Retrievalcited by 41
  10. 2021R2-D2: A Modular Baseline for Open-Domain Question Answeringcited by 37
  11. 2022Towards Robust Ranker for Text Retrievalcited by 37
  12. 2025A Survey of Multimodal Retrieval-Augmented Generationcited by 37
  13. 2024The Chronicles of RAG: The Retriever, the Chunk and the Generatorcited by 34
  14. 2024Automated Focused Feedback Generation for Scientific Writing Assistancecited by 33
  15. 2025Rank-K: Test-Time Reasoning for Listwise Rerankingcited by 29
  16. 2021Retrieve Fast, Rerank Smart: Cooperative and Joint Approaches for Improved Cross-Modal Retrievalcited by 28
  17. 2024APEER: Automatic Prompt Engineering Enhances Large Language Model Rerankingcited by 28
  18. 2024Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generationcited by 27
  19. 2022Towards Best Practices for Training Multilingual Dense Retrieval Modelscited by 26
  20. 2023When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasetscited by 26
  21. 2021On Cross-Lingual Retrieval with Multilingual Text Encoderscited by 22
  22. 2024Translate-Distill: Learning Cross-Language Dense Retrieval by Translation and Distillationcited by 22
  23. 2025SkillFlow: Scalable and Efficient Agent Skill Retrieval Systemcited by 22
  24. 2024Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challengescited by 20
  25. 2024Ranked List Truncation for Large Language Model-based Re-Rankingcited by 20
  26. 2024Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Modelscited by 20
  27. 2023Large Search Model: Redefining Search Stack in the Era of LLMscited by 18
  28. 2023GAR-meets-RAG Paradigm for Zero-Shot Information Retrievalcited by 18
  29. 2022PMC-Patients: A Large-scale Dataset of Patient Summaries and Relations for Benchmarking Retrieval-based Clinical Decision Support Systemscited by 17
  30. 2022Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrievalcited by 17
  31. 2024Metasql: A Generate-then-Rank Framework for Natural Language to SQL Translationcited by 17
  32. 2024Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankerscited by 17
  33. 2021Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrievalcited by 16
  34. 2021Article Reranking by Memory-Enhanced Key Sentence Matching for Detecting Previously Fact-Checked Claimscited by 16
  35. 2024Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAGcited by 16
  36. 2021Text-to-Text Multi-view Learning for Passage Re-rankingcited by 14
  37. 2022C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrievalcited by 14
  38. 2025Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systemscited by 14

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