mlsanityData to 7 Oct 2026

HYRR: Hybrid Infused Reranking for Passage Retrieval

arXiv 2212.10528 ↗First posted 20 Dec 2022cs.CL cs.IRcited by 6

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Abstract (arXiv)

We present Hybrid Infused Reranking for Passages Retrieval (HYRR), a framework for training rerankers based on a hybrid of BM25 and neural retrieval models. Retrievers based on hybrid models have been shown to outperform both BM25 and neural models alone. Our approach exploits this improved performance when training a reranker, leading to a robust reranking model. The reranker, a cross-attention neural model, is shown to be robust to different first-stage retrieval systems, achieving better performance than rerankers simply trained upon the first-stage retrievers in the multi-stage systems. We present evaluations on a supervised passage retrieval task using MS MARCO and zero-shot retrieval tasks using BEIR. The empirical results show strong performance on both evaluations.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 29 of its 44 references that are in the map. First posted on arXiv 20 Dec 2022.

Builds on

29 of 44 references.

References · 29

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  12. 2020RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answeringcited by 410
17 more
  1. 2020Document Ranking with a Pretrained Sequence-to-Sequence Modelcited by 373
  2. 2022Promptagator: Few-shot Dense Retrieval From 8 Examplescited by 233
  3. 2017Efficient Natural Language Response Suggestion for Smart Replycited by 228
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  5. 2019Multi-Stage Document Ranking with BERTcited by 200
  6. 2021PAQ: 65 Million Probably-Asked Questions and What You Can Do With Themcited by 198
  7. 2021RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-rankingcited by 175
  8. 2022Improving Passage Retrieval with Zero-Shot Question Generationcited by 164
  9. 2020Embedding-based Retrieval in Facebook Searchcited by 155
  10. 2019Synthetic QA Corpora Generation with Roundtrip Consistencycited by 143
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  12. 2021The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Modelscited by 81
  13. 2021Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipelinecited by 65
  14. 2022InPars: Data Augmentation for Information Retrieval using Large Language Modelscited by 60
  15. 2022Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Modelscited by 26
  16. 2022HLATR: Enhance Multi-stage Text Retrieval with Hybrid List Aware Transformer Rerankingcited by 19
  17. 2022No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrievalcited by 17

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 2; 2026: 2.

6 papers.

  1. 2025A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigmscited by 17
  2. 2025Retrieval Augmented Question Answering: When Should LLMs Admit Ignorance?cited by 2
  3. 2024MST-R: Multi-Stage Tuning for Retrieval Systems and Metric Evaluationcited by 0
  4. 2024Enabling Low-Resource Language Retrieval: Establishing Baselines for Urdu MS MARCOcited by 0
  5. 2026Efficient K-generalizable Learned Searchcited by 0
  6. 2026Distinguishing Right from Wrong in Debates: Attribution Analysis of Chinese Harmful Memescited by 0