mlsanityData to 7 Oct 2026

Multi-CPR: A Multi Domain Chinese Dataset for Passage Retrieval

arXiv 2203.03367 ↗First posted 7 Mar 2022cs.IR cs.CLcited by 26

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Abstract (arXiv)

Passage retrieval is a fundamental task in information retrieval (IR) research, which has drawn much attention recently. In the English field, the availability of large-scale annotated dataset (e.g, MS MARCO) and the emergence of deep pre-trained language models (e.g, BERT) has resulted in a substantial improvement of existing passage retrieval systems. However, in the Chinese field, especially for specific domains, passage retrieval systems are still immature due to quality-annotated dataset being limited by scale. Therefore, in this paper, we present a novel multi-domain Chinese dataset for passage retrieval (Multi-CPR). The dataset is collected from three different domains, including E-commerce, Entertainment video and Medical. Each dataset contains millions of passages and a certain amount of human annotated query-passage related pairs. We implement various representative passage retrieval methods as baselines. We find that the performance of retrieval models trained on dataset from general domain will inevitably decrease on specific domain. Nevertheless, a passage retrieval system built on in-domain annotated dataset can achieve significant improvement, which indeed demonstrates the necessity of domain labeled data for further optimization. We hope the release of the Multi-CPR dataset could benchmark Chinese passage retrieval task in specific domain and also make advances for future studies.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). Builds on 39 of its 56 references that are in the map. First posted on arXiv 7 Mar 2022.

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39 of 56 references.

References · 39

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  4. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  5. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  6. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,801
  7. 2020DeBERTa: Decoding-enhanced BERT with Disentangled Attentioncited by 2,157
  8. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,591
  9. 2020Don't Stop Pretraining: Adapt Language Models to Domains and Taskscited by 1,548
  10. 2015Teaching Machines to Read and Comprehendcited by 1,039
  11. 2020Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrievalcited by 846
  12. 2019Passage Re-ranking with BERTcited by 629
27 more
  1. 2020RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answeringcited by 410
  2. 2019Document Expansion by Query Predictioncited by 225
  3. 2020Sparse, Dense, and Attentional Representations for Text Retrievalcited by 213
  4. 2021Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrievalcited by 203
  5. 2021RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-rankingcited by 175
  6. 2021Condenser: a Pre-training Architecture for Dense Retrievalcited by 162
  7. 2021Optimizing Dense Retrieval Model Training with Hard Negativescited by 154
  8. 2021COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted Listcited by 113
  9. 2019Deeper Text Understanding for IR with Contextual Neural Language Modelingcited by 111
  10. 2017DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applicationscited by 110
  11. 2021Adversarial Retriever-Ranker for dense text retrievalcited by 82
  12. 2015A Hierarchical Recurrent Encoder-Decoder For Generative Context-Aware Query Suggestioncited by 68
  13. 2019Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrievalcited by 65
  14. 2021Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipelinecited by 65
  15. 2021Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representationscited by 60
  16. 2021Efficient Passage Retrieval with Hashing for Open-domain Question Answeringcited by 53
  17. 2020Leveraging Semantic and Lexical Matching to Improve the Recall of Document Retrieval Systems: A Hybrid Approachcited by 31
  18. 2015Applying Deep Learning to Answer Selection: A Study and An Open Taskcited by 24
  19. 2017Learning to Attend, Copy, and Generate for Session-Based Query Suggestioncited by 22
  20. 2018WikiPassageQA: A Benchmark Collection for Research on Non-factoid Answer Passage Retrievalcited by 19
  21. 2020Conceptualized Representation Learning for Chinese Biomedical Text Miningcited by 19
  22. 2018Neural Adaptation Layers for Cross-domain Named Entity Recognitioncited by 15
  23. 2020A Sentence Cloze Dataset for Chinese Machine Reading Comprehensioncited by 14
  24. 2018Retrieve-and-Read: Multi-task Learning of Information Retrieval and Reading Comprehensioncited by 9
  25. 2021Encoder Adaptation of Dense Passage Retrieval for Open-Domain Question Answeringcited by 8
  26. 2020Coupling Distant Annotation and Adversarial Training for Cross-Domain Chinese Word Segmentationcited by 6
  27. 2019Investigating the Successes and Failures of BERT for Passage Re-Rankingcited by 2

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Citing papers per year: 2022: 2; 2023: 6; 2024: 9; 2025: 4; 2026: 5.

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  1. 2023Towards General Text Embeddings with Multi-stage Contrastive Learningcited by 705
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  3. 2024mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrievalcited by 233
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  6. 2025KaLM-Embedding-V2: Superior Training Techniques and Data Inspire A Versatile Embedding Modelcited by 35
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  9. 2024Piccolo2: General Text Embedding with Multi-task Hybrid Loss Trainingcited by 10
  10. 2024ProductAgent: Benchmarking Conversational Product Search Agent with Asking Clarification Questionscited by 10
  11. 2026F2LLM-v2: Inclusive, Performant, and Efficient Embeddings for a Multilingual Worldcited by 10
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  2. 2022Retrieval Oriented Masking Pre-training Language Model for Dense Passage Retrievalcited by 4
  3. 2024BSharedRAG: Backbone Shared Retrieval-Augmented Generation for the E-commerce Domaincited by 4
  4. 2023Challenging Decoder helps in Masked Auto-Encoder Pre-training for Dense Passage Retrievalcited by 3
  5. 2023Text Representation Distillation via Information Bottleneck Principlecited by 3
  6. 2024UniRetriever: Multi-task Candidates Selection for Various Context-Adaptive Conversational Retrievalcited by 3
  7. 2025Dense Retrievers Can Fail on Simple Queries: Revealing The Granularity Dilemma of Embeddingscited by 2
  8. 2025CoDiEmb: A Collaborative yet Distinct Framework for Unified Representation Learning in Information Retrieval and Semantic Textual Similaritycited by 2
  9. 2024Unlocking Multi-View Insights in Knowledge-Dense Retrieval-Augmented Generationcited by 1
  10. 2026SQuTR: A Robustness Benchmark for Spoken Query to Text Retrieval under Acoustic Noisecited by 1
  11. 2025ICA-RAG: Information Completeness Guided Adaptive Retrieval-Augmented Generation for Disease Diagnosiscited by 0
  12. 2026Sandwich Reasoning: An Answer-Reasoning-Answer Approach for Low-Latency Query Correctioncited by 0
  13. 2026ML-Embed: Inclusive and Efficient Embeddings for a Multilingual Worldcited by 0
  14. 2026KaLM-Reranker-V1: Fast but Not Late Interaction for Compressed Document Rerankingcited by 0