EMNLP 2022main23 citations

DuReader-Retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine

Yifu Qiu, Hongyu Li, Yingqi Qu, Ying Chen, QiaoQiao She, Jing Liu, Hua Wu, Haifeng Wang

Abstract

In this paper, we present DuReader-retrieval, a large-scale Chinese dataset for passage retrieval. DuReader-retrieval contains more than 90K queries and over 8M unique passages from a commercial search engine. To alleviate the shortcomings of other datasets and ensure the quality of our benchmark, we (1) reduce the false negatives in development and test sets by manually annotating results pooled from multiple retrievers, and (2) remove the training queries that are semantically similar to the development and testing queries. Additionally, we provide two out-of-domain testing sets for cross-domain evaluation, as well as a set of human translated queries for for cross-lingual retrieval evaluation. The experiments demonstrate that DuReader-retrieval is challenging and a number of problems remain unsolved, such as the salient phrase mismatch and the syntactic mismatch between queries and paragraphs. These experiments also show that dense retrievers do not generalize well across domains, and cross-lingual retrieval is essentially challenging. DuReader-retrieval is publicly available at https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval.

BibTeX
@inproceedings{qiu-etal-2022-dureader,
    title = "{D}u{R}eader-Retrieval: A Large-scale {C}hinese Benchmark for Passage Retrieval from Web Search Engine",
    author = "Qiu, Yifu  and
      Li, Hongyu  and
      Qu, Yingqi  and
      Chen, Ying  and
      She, QiaoQiao  and
      Liu, Jing  and
      Wu, Hua  and
      Wang, Haifeng",
    editor = "Goldberg, Yoav  and
      Kozareva, Zornitsa  and
      Zhang, Yue",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.emnlp-main.357/",
    doi = "10.18653/v1/2022.emnlp-main.357",
    pages = "5326--5338"
}
DuReader-Retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine · EMNLP 2022