mlsanityData to 14 Oct 2026

Rider: Reader-Guided Passage Reranking for Open-Domain Question Answering

arXiv 2101.00294 ↗First posted 1 Jan 2021cs.CL cs.AI cs.IRcited by 28

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Abstract (arXiv)

Current open-domain question answering systems often follow a Retriever-Reader architecture, where the retriever first retrieves relevant passages and the reader then reads the retrieved passages to form an answer. In this paper, we propose a simple and effective passage reranking method, named Reader-guIDEd Reranker (RIDER), which does not involve training and reranks the retrieved passages solely based on the top predictions of the reader before reranking. We show that RIDER, despite its simplicity, achieves 10 to 20 absolute gains in top-1 retrieval accuracy and 1 to 4 Exact Match (EM) gains without refining the retriever or reader. In addition, RIDER, without any training, outperforms state-of-the-art transformer-based supervised rerankers. Remarkably, RIDER achieves 48.3 EM on the Natural Questions dataset and 66.4 EM on the TriviaQA dataset when only 1,024 tokens (7.8 passages on average) are used as the reader input after passage reranking.

Key facts. Cited by 28 papers in the map (data through 14 Oct 2026). Builds on 25 of its 28 references that are in the map. First posted on arXiv 1 Jan 2021.

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25 of 28 references.

References · 25

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  4. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  5. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
  6. 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,955
  7. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,141
  8. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,210
  9. 2020How Much Knowledge Can You Pack Into the Parameters of a Language Model?cited by 719
  10. 2019Latent Retrieval for Weakly Supervised Open Domain Question Answeringcited by 695
  11. 2019Passage Re-ranking with BERTcited by 645
  12. 2020AmbigQA: Answering Ambiguous Open-domain Questionscited by 390
13 more
  1. 2020Document Ranking with a Pretrained Sequence-to-Sequence Modelcited by 376
  2. 2020Distilling Knowledge from Reader to Retriever for Question Answeringcited by 226
  3. 2020Generation-Augmented Retrieval for Open-domain Question Answeringcited by 186
  4. 2019Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answeringcited by 147
  5. 2019A Discrete Hard EM Approach for Weakly Supervised Question Answeringcited by 78
  6. 2019Knowledge Guided Text Retrieval and Reading for Open Domain Question Answeringcited by 59
  7. 2019Understanding the Behaviors of BERT in Rankingcited by 49
  8. 2019Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answeringcited by 48
  9. 2020Is Retriever Merely an Approximator of Reader?cited by 30
  10. 2017Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answeringcited by 24
  11. 2018Ranking Paragraphs for Improving Answer Recall in Open-Domain Question Answeringcited by 24
  12. 2017R3: Reinforced Reader-Ranker for Open-Domain Question Answeringcited by 9
  13. 2020RECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answeringcited by 9

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Citing papers per year: 2021: 7; 2022: 5; 2023: 8; 2024: 5; 2025: 3.

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  1. 2021RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-rankingcited by 176
  2. 2023CoLT5: Faster Long-Range Transformers with Conditional Computationcited by 84
  3. 2021Adversarial Retriever-Ranker for dense text retrievalcited by 83
  4. 2023Learning to Filter Context for Retrieval-Augmented Generationcited by 83
  5. 2021KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answeringcited by 67
  6. 2024SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMscited by 67
  7. 2021R2-D2: A Modular Baseline for Open-Domain Question Answeringcited by 37
  8. 2024Grounding Language Model with Chunking-Free In-Context Retrievalcited by 30
  9. 2023Large Language Models are Built-in Autoregressive Search Enginescited by 27
  10. 2023IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositionscited by 26
  11. 2024Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMscited by 24
  12. 2022Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answeringcited by 22
16 more
  1. 2021You Only Need One Model for Open-domain Question Answeringcited by 17
  2. 2023Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your computecited by 17
  3. 2022CiteSum: Citation Text-guided Scientific Extreme Summarization and Domain Adaptation with Limited Supervisioncited by 15
  4. 2023Expand, Rerank, and Retrieve: Query Reranking for Open-Domain Question Answeringcited by 15
  5. 2022Augmenting Document Representations for Dense Retrieval with Interpolation and Perturbationcited by 10
  6. 2022Open-Domain Conversational Question Answering with Historical Answerscited by 8
  7. 2023GLIMMER: generalized late-interaction memory rerankercited by 7
  8. 2024Self-Calibrated Listwise Reranking with Large Language Modelscited by 7
  9. 2021Pruning the Index Contents for Memory Efficient Open-Domain QAcited by 6
  10. 2024Multimodal Reranking for Knowledge-Intensive Visual Question Answeringcited by 6
  11. 2025RGAR: Recurrence Generation-augmented Retrieval for Factual-aware Medical Question Answeringcited by 5
  12. 2021Training Adaptive Computation for Open-Domain Question Answering with Computational Constraintscited by 4
  13. 2022Two-Step Question Retrieval for Open-Domain QAcited by 4
  14. 2023Strong and Efficient Baselines for Open Domain Conversational Question Answeringcited by 2
  15. 2025Oreo: A Plug-in Context Reconstructor to Enhance Retrieval-Augmented Generationcited by 1
  16. 2025Learning to Extract Rational Evidence via Reinforcement Learning for Retrieval-Augmented Generationcited by 1