# Joint Passage Ranking for Diverse Multi-Answer Retrieval

arXiv: https://arxiv.org/abs/2104.08445 · HTML: https://mlsanity.com/paper/2104.08445/

## Key facts

- Cited by 43 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 38 references that are in the map.
- First posted on arXiv 17 Apr 2021.

## Builds on (most cited first, 22 of 22)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://mlsanity.com/paper/2005.11401/) (2020)
- [Dense Passage Retrieval for Open-Domain Question Answering](https://mlsanity.com/paper/2004.04906/) (2020)
- [REALM: Retrieval-Augmented Language Model Pre-Training](https://mlsanity.com/paper/2002.08909/) (2020)
- [Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation](https://mlsanity.com/paper/1609.08144/) (2016)
- [Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering](https://mlsanity.com/paper/2007.01282/) (2020)
- [Pointer Networks](https://mlsanity.com/paper/1506.03134/) (2015)
- [Reading Wikipedia to Answer Open-Domain Questions](https://mlsanity.com/paper/1704.00051/) (2017)
- [Latent Retrieval for Weakly Supervised Open Domain Question Answering](https://mlsanity.com/paper/1906.00300/) (2019)
- [Passage Re-ranking with BERT](https://mlsanity.com/paper/1901.04085/) (2019)
- [AmbigQA: Answering Ambiguous Open-domain Questions](https://mlsanity.com/paper/2004.10645/) (2020)
- [Document Ranking with a Pretrained Sequence-to-Sequence Model](https://mlsanity.com/paper/2003.06713/) (2020)
- [Sparse, Dense, and Attentional Representations for Text Retrieval](https://mlsanity.com/paper/2005.00181/) (2020)
- [Mesh-TensorFlow: Deep Learning for Supercomputers](https://mlsanity.com/paper/1811.02084/) (2018)
- [Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval](https://mlsanity.com/paper/2009.12756/) (2020)
- [Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering](https://mlsanity.com/paper/1911.10470/) (2019)
- [Compositional Questions Do Not Necessitate Multi-hop Reasoning](https://mlsanity.com/paper/1906.02900/) (2019)
- [Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval](https://mlsanity.com/paper/2101.00436/) (2021)
- [Understanding Dataset Design Choices for Multi-hop Reasoning](https://mlsanity.com/paper/1904.12106/) (2019)
- [Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction](https://mlsanity.com/paper/2011.13137/) (2020)
- [Managing Diversity in Airbnb Search](https://mlsanity.com/paper/2004.02621/) (2020)

## Built on by (most cited first, 30 of 43)

- [RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval](https://mlsanity.com/paper/2401.18059/) (2024)
- [ASQA: Factoid Questions Meet Long-Form Answers](https://mlsanity.com/paper/2204.06092/) (2022)
- [Diverse Demonstrations Improve In-context Compositional Generalization](https://mlsanity.com/paper/2212.06800/) (2022)
- [Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?](https://mlsanity.com/paper/2406.13121/) (2024)
- [Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models](https://mlsanity.com/paper/2310.14696/) (2023)
- [LidarCLIP or: How I Learned to Talk to Point Clouds](https://mlsanity.com/paper/2212.06858/) (2022)
- [QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations](https://mlsanity.com/paper/2305.11694/) (2023)
- [Retrieval-guided Counterfactual Generation for QA](https://mlsanity.com/paper/2110.07596/) (2021)
- [NodeRAG: Structuring Graph-based RAG with Heterogeneous Nodes](https://mlsanity.com/paper/2504.11544/) (2025)
- [You can't pick your neighbors, or can you? When and how to rely on retrieval in the kNN-LM](https://mlsanity.com/paper/2210.15859/) (2022)
- [MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspective](https://mlsanity.com/paper/2204.04391/) (2022)
- [Generative Knowledge Selection for Knowledge-Grounded Dialogues](https://mlsanity.com/paper/2304.04836/) (2023)
- [Adaptive Question Answering: Enhancing Language Model Proficiency for Addressing Knowledge Conflicts with Source Citations](https://mlsanity.com/paper/2410.04241/) (2024)
- [Merging Facts, Crafting Fallacies: Evaluating the Contradictory Nature of Aggregated Factual Claims in Long-Form Generations](https://mlsanity.com/paper/2402.05629/) (2024)
- [Answering Ambiguous Questions via Iterative Prompting](https://mlsanity.com/paper/2307.03897/) (2023)
- [Answering Open-Domain Multi-Answer Questions via a Recall-then-Verify Framework](https://mlsanity.com/paper/2110.08544/) (2021)
- [Open-World Evaluation for Retrieving Diverse Perspectives](https://mlsanity.com/paper/2409.18110/) (2024)
- [Diversify-verify-adapt: Efficient and Robust Retrieval-Augmented Ambiguous Question Answering](https://mlsanity.com/paper/2409.02361/) (2024)
- [Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models](https://mlsanity.com/paper/2505.03075/) (2025)
- [SetBERT: Enhancing Retrieval Performance for Boolean Logic and Set Operation Queries](https://mlsanity.com/paper/2406.17282/) (2024)
- [Beyond Single Embeddings: Capturing Diverse Targets with Multi-Query Retrieval](https://mlsanity.com/paper/2511.02770/) (2025)
- [Answering Ambiguous Questions with a Database of Questions, Answers, and Revisions](https://mlsanity.com/paper/2308.08661/) (2023)
- [Enhancing Long Context Performance in LLMs Through Inner Loop Query Mechanism](https://mlsanity.com/paper/2410.12859/) (2024)
- [DTCRS: Dynamic Tree Construction for Recursive Summarization](https://mlsanity.com/paper/2604.07012/) (2026)
- [Grounded Keys-to-Text Generation: Towards Factual Open-Ended Generation](https://mlsanity.com/paper/2212.01956/) (2022)
- [CORG: Generating Answers from Complex, Interrelated Contexts](https://mlsanity.com/paper/2505.00023/) (2025)
- [Diverse Multi-Answer Retrieval with Determinantal Point Processes](https://mlsanity.com/paper/2211.16029/) (2022)
- [Model Analysis & Evaluation for Ambiguous Question Answering](https://mlsanity.com/paper/2305.12483/) (2023)
- [Corpus-informed Retrieval Augmented Generation of Clarifying Questions](https://mlsanity.com/paper/2409.18575/) (2024)
- [Agentic Verification for Ambiguous Query Disambiguation](https://mlsanity.com/paper/2502.10352/) (2025)

## 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.