mlsanityData to 7 Oct 2026

Referral Augmentation for Zero-Shot Information Retrieval

arXiv 2305.15098 ↗First posted 24 May 2023cs.CLcited by 3

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Abstract (arXiv)

We propose Referral-Augmented Retrieval (RAR), a simple technique that concatenates document indices with referrals, i.e. text from other documents that cite or link to the given document, to provide significant performance gains for zero-shot information retrieval. The key insight behind our method is that referrals provide a more complete, multi-view representation of a document, much like incoming page links in algorithms like PageRank provide a comprehensive idea of a webpage's importance. RAR works with both sparse and dense retrievers, and outperforms generative text expansion techniques such as DocT5Query and Query2Doc a 37% and 21% absolute improvement on ACL paper retrieval Recall@10 -- while also eliminating expensive model training and inference. We also analyze different methods for multi-referral aggregation and show that RAR enables up-to-date information retrieval without re-training.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 27 of its 46 references that are in the map. First posted on arXiv 24 May 2023.

Builds on

27 of 46 references.

References · 27

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15 more
  1. 2020ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERTcited by 1,160
  2. 2023In-Context Retrieval-Augmented Language Modelscited by 694
  3. 2021Editing Factual Knowledge in Language Modelscited by 548
  4. 2022Precise Zero-Shot Dense Retrieval without Relevance Labelscited by 508
  5. 2020SPECTER: Document-level Representation Learning using Citation-informed Transformerscited by 426
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  12. 2022RAW-GNN: RAndom Walk Aggregation based Graph Neural Networkcited by 25
  13. 2023Large Language Models are Strong Zero-Shot Retrievercited by 25
  14. 2021Local Citation Recommendation with Hierarchical-Attention Text Encoder and SciBERT-based Rerankingcited by 18
  15. 2022Pre-training for Information Retrieval: Are Hyperlinks Fully Explored?cited by 2

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Citing papers per year: 2023: 1; 2024: 2.

3 papers.

  1. 2023Cognitive Architectures for Language Agentscited by 422
  2. 2024LitSearch: A Retrieval Benchmark for Scientific Literature Searchcited by 47
  3. 2024CiteME: Can Language Models Accurately Cite Scientific Claims?cited by 45