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PACRR: A Position-Aware Neural IR Model for Relevance Matching

arXiv 1704.03940 ↗First posted 12 Apr 2017cs.IR cs.CLcited by 22

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Abstract (arXiv)

In order to adopt deep learning for information retrieval, models are needed that can capture all relevant information required to assess the relevance of a document to a given user query. While previous works have successfully captured unigram term matches, how to fully employ position-dependent information such as proximity and term dependencies has been insufficiently explored. In this work, we propose a novel neural IR model named PACRR aiming at better modeling position-dependent interactions between a query and a document. Extensive experiments on six years' TREC Web Track data confirm that the proposed model yields better results under multiple benchmarks.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Apr 2017.

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Citing papers per year: 2021: 10; 2022: 3; 2023: 4; 2024: 1; 2025: 3; 2026: 1.

22 papers.

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  1. 2022Promptagator: Few-shot Dense Retrieval From 8 Examplescited by 235
  2. 2021Biomedical Question Answering: A Survey of Approaches and Challengescited by 46
  3. 2022Transfer Learning Approaches for Building Cross-Language Dense Retrieval Modelscited by 36
  4. 2021Rethinking Search: Making Domain Experts out of Dilettantescited by 18
  5. 2021Neural ranking models for document retrievalcited by 16
  6. 2021Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitationscited by 13
  7. 2021Studying Catastrophic Forgetting in Neural Ranking Modelscited by 9
  8. 2023Finding the Law: Enhancing Statutory Article Retrieval via Graph Neural Networkscited by 9
  9. 2021Match-Ignition: Plugging PageRank into Transformer for Long-form Text Matchingcited by 5
  10. 2024DREQ: Document Re-Ranking Using Entity-based Query Understandingcited by 5
  11. 2022Continual Learning of Long Topic Sequences in Neural Information Retrievalcited by 4
  12. 2023Machine Translation Impact in E-commerce Multilingual Searchcited by 4
10 more
  1. 2021A Neural Model for Joint Document and Snippet Ranking in Question Answering for Large Document Collectionscited by 2
  2. 2021Embracing Structure in Data for Billion-Scale Semantic Product Searchcited by 2
  3. 2023LADER: Log-Augmented DEnse Retrieval for Biomedical Literature Searchcited by 2
  4. 2021YES SIR!Optimizing Semantic Space of Negatives with Self-Involvement Rankercited by 1
  5. 2021Intent-based Product Collections for E-commerce using Pretrained Language Modelscited by 1
  6. 2023Improving Out-of-Distribution Generalization of Neural Rerankers with Contextualized Late Interactioncited by 1
  7. 2025QDER: Query-Specific Document and Entity Representations for Multi-Vector Document Re-Rankingcited by 1
  8. 2026RANKVIDEO: Reasoning Reranking for Text-to-Video Retrievalcited by 1
  9. 2025REGENT: Relevance-Guided Attention for Entity-Aware Multi-Vector Neural Re-Rankingcited by 0
  10. 2025Controlling Gender Bias in Retrieval via a Backpack Architecturecited by 0