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Joint Passage Ranking for Diverse Multi-Answer Retrieval

arXiv 2104.08445 ↗First posted 17 Apr 2021cs.CL cs.AIcited by 43

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Abstract (arXiv)

We study multi-answer retrieval, an under-explored problem that requires retrieving passages to cover multiple distinct answers for a given question. This task requires joint modeling of retrieved passages, as models should not repeatedly retrieve passages containing the same answer at the cost of missing a different valid answer. In this paper, we introduce JPR, the first joint passage retrieval model for multi-answer retrieval. JPR makes use of an autoregressive reranker that selects a sequence of passages, each conditioned on previously selected passages. JPR is trained to select passages that cover new answers at each timestep and uses a tree-decoding algorithm to enable flexibility in the degree of diversity. Compared to prior approaches, JPR achieves significantly better answer coverage on three multi-answer datasets. When combined with downstream question answering, the improved retrieval enables larger answer generation models since they need to consider fewer passages, establishing a new state-of-the-art.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Builds on 22 of its 38 references that are in the map. First posted on arXiv 17 Apr 2021.

Builds on

22 of 38 references.

References · 22

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
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10 more
  1. 2020Document Ranking with a Pretrained Sequence-to-Sequence Modelcited by 373
  2. 2020Sparse, Dense, and Attentional Representations for Text Retrievalcited by 213
  3. 2018Mesh-TensorFlow: Deep Learning for Supercomputerscited by 168
  4. 2020Answering Complex Open-Domain Questions with Multi-Hop Dense Retrievalcited by 160
  5. 2019Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answeringcited by 147
  6. 2019Compositional Questions Do Not Necessitate Multi-hop Reasoningcited by 87
  7. 2021Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrievalcited by 63
  8. 2019Understanding Dataset Design Choices for Multi-hop Reasoningcited by 50
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Citing papers per year: 2021: 2; 2022: 8; 2023: 7; 2024: 12; 2025: 8; 2026: 6.

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  1. 2024RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrievalcited by 519
  2. 2022ASQA: Factoid Questions Meet Long-Form Answerscited by 231
  3. 2022Diverse Demonstrations Improve In-context Compositional Generalizationcited by 136
  4. 2024Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?cited by 53
  5. 2023Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Modelscited by 42
  6. 2022LidarCLIP or: How I Learned to Talk to Point Cloudscited by 33
  7. 2023QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operationscited by 30
  8. 2021Retrieval-guided Counterfactual Generation for QAcited by 28
  9. 2025NodeRAG: Structuring Graph-based RAG with Heterogeneous Nodescited by 25
  10. 2022You can't pick your neighbors, or can you? When and how to rely on retrieval in the kNN-LMcited by 18
  11. 2022MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspectivecited by 17
  12. 2023Generative Knowledge Selection for Knowledge-Grounded Dialoguescited by 15
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  2. 2024Merging Facts, Crafting Fallacies: Evaluating the Contradictory Nature of Aggregated Factual Claims in Long-Form Generationscited by 14
  3. 2023Answering Ambiguous Questions via Iterative Promptingcited by 13
  4. 2021Answering Open-Domain Multi-Answer Questions via a Recall-then-Verify Frameworkcited by 11
  5. 2024Open-World Evaluation for Retrieving Diverse Perspectivescited by 11
  6. 2024Diversify-verify-adapt: Efficient and Robust Retrieval-Augmented Ambiguous Question Answeringcited by 10
  7. 2025Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Modelscited by 9
  8. 2024SetBERT: Enhancing Retrieval Performance for Boolean Logic and Set Operation Queriescited by 5
  9. 2025Beyond Single Embeddings: Capturing Diverse Targets with Multi-Query Retrievalcited by 5
  10. 2023Answering Ambiguous Questions with a Database of Questions, Answers, and Revisionscited by 4
  11. 2024Enhancing Long Context Performance in LLMs Through Inner Loop Query Mechanismcited by 4
  12. 2026DTCRS: Dynamic Tree Construction for Recursive Summarizationcited by 4
  13. 2022Grounded Keys-to-Text Generation: Towards Factual Open-Ended Generationcited by 3
  14. 2025CORG: Generating Answers from Complex, Interrelated Contextscited by 3
  15. 2022Diverse Multi-Answer Retrieval with Determinantal Point Processescited by 2
  16. 2023Model Analysis & Evaluation for Ambiguous Question Answeringcited by 2
  17. 2024Corpus-informed Retrieval Augmented Generation of Clarifying Questionscited by 2
  18. 2025Agentic Verification for Ambiguous Query Disambiguationcited by 2
  19. 2022Answer Consolidation: Formulation and Benchmarkingcited by 1
  20. 2025Inter-Passage Verification for Multi-evidence Multi-answer QAcited by 1
  21. 2026RVR: Retrieve-Verify-Retrieve for Comprehensive Question Answeringcited by 1
  22. 2023Dialogue-Contextualized Re-ranking for Medical History-Takingcited by 0
  23. 2024GEM-RAG: Graphical Eigen Memories For Retrieval Augmented Generationcited by 0
  24. 2024PECAN: LLM-Guided Dynamic Progress Control with Attention-Guided Hierarchical Weighted Graph for Long-Document QAcited by 0
  25. 2024Retrieving Contextual Information for Long-Form Question Answering using Weak Supervisioncited by 0
  26. 2025GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Frameworkcited by 0
  27. 2025Evaluation of retrieval-based QA on QUEST-LOFTcited by 0
  28. 2026Clarify, Abstain or Answer? Strategising in Conversation with Belief-Augmented Generationcited by 0
  29. 2026Search for Coverage: Learning Coverage-Aware Retrieval with Augmented Sub-Question Answerabilitycited by 0
  30. 2026A knowledge-guided agentic framework for mitigating patient-context ambiguity in health queriescited by 0
  31. 2026Beyond One-Shot Expansion: Contrastive Evidence Exploration for Multi-Hop Retrievalcited by 0