mlsanityData to 7 Oct 2026

Typo-Robust Representation Learning for Dense Retrieval

arXiv 2306.10348 ↗First posted 17 Jun 2023cs.IR cs.CLcited by 6

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Abstract (arXiv)

Dense retrieval is a basic building block of information retrieval applications. One of the main challenges of dense retrieval in real-world settings is the handling of queries containing misspelled words. A popular approach for handling misspelled queries is minimizing the representations discrepancy between misspelled queries and their pristine ones. Unlike the existing approaches, which only focus on the alignment between misspelled and pristine queries, our method also improves the contrast between each misspelled query and its surrounding queries. To assess the effectiveness of our proposed method, we compare it against the existing competitors using two benchmark datasets and two base encoders. Our method outperforms the competitors in all cases with misspelled queries. Our code and models are available at https://github. com/panuthept/DST-DenseRetrieval.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 17 of its 19 references that are in the map. First posted on arXiv 17 Jun 2023.

Builds on

17 of 19 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  3. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,591
  4. 2020ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERTcited by 1,160
  5. 2020Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrievalcited by 846
  6. 2020RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answeringcited by 410
  7. 2021RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-rankingcited by 175
  8. 2020CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characterscited by 87
  9. 2021PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrievalcited by 50
  10. 2022Tevatron: An Efficient and Flexible Toolkit for Dense Retrievalcited by 47
  11. 2020RepBERT: Contextualized Text Embeddings for First-Stage Retrievalcited by 46
  12. 2017Dual Supervised Learningcited by 33
5 more
  1. 2021Evaluating the Robustness of Retrieval Pipelines with Query Variation Generatorscited by 33
  2. 2021Dealing with Typos for BERT-based Passage Retrieval and Rankingcited by 23
  3. 2022Analysing the Robustness of Dual Encoders for Dense Retrieval Against Misspellingscited by 23
  4. 2022CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typoscited by 22
  5. 2021More Robust Dense Retrieval with Contrastive Dual Learningcited by 15

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 1; 2026: 3.

6 papers.

  1. 2023Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-agent LLMcited by 18
  2. 2024Robust Neural Information Retrieval: An Adversarial and Out-of-distribution Perspectivecited by 15
  3. 2025Beyond Monolingual Assumptions: A Survey of Code-Switched NLP in the Era of Large Language Models across Modalitiescited by 4
  4. 2026On the Robustness of LLM-Based Dense Retrievers: A Systematic Analysis of Generalizability and Stabilitycited by 0
  5. 2026Hypencoder Revisited: Reproducibility and Analysis of Non-Linear Scoring for First-Stage Retrievalcited by 0
  6. 2026Retrieved But Not Reliable: A Survey on Attacks, and Defenses in Retrieval-Augmented Generationcited by 0