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SentBench: Comprehensive Evaluation of Self-Supervised Sentence Representation with Benchmark Construction

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Chinese Computational Linguistics (CCL 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14232))

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Abstract

Self-supervised learning has been widely used to learn effective sentence representations. Previous evaluation of sentence representations mainly focuses on the limited combination of tasks and paradigms while failing to evaluate their effectiveness in a wider range of application scenarios. Such divergences prevent us from understanding the limitations of current sentence representations, as well as the connections between learning approaches and downstream applications. In this paper, we propose SentBench, a new comprehensive benchmark to evaluate sentence representations. SentBench covers 12 kinds of tasks and evaluates sentence representations with three types of different downstream application paradigms. Based on SentBench, we re-evaluate several frequently used self-supervised sentence representation learning approaches. Experiments show that SentBench can effectively evaluate sentence representations from multiple perspectives, and the performance on SentBench leads to some novel findings which enlighten future researches.

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Notes

  1. 1.

    https://github.com/facebookresearch/SentEval.

  2. 2.

    We discard the MLP layer over [CLS] for evaluation.

  3. 3.

    https://github.com/makcedward/nlpaug.

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Acknowledgements

We sincerely thank the reviewers for their insightful comments and valuable suggestions. This research work is supported by the National Natural Science Foundation of China under Grants no. U1936207, 62122077 and 62106251.

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Authors and Affiliations

  1. Chinese Information Processing Laboratory, Beijing, China

    Xiaoming Liu, Hongyu Lin, Xianpei Han & Le Sun

  2. State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China

    Xianpei Han & Le Sun

  3. University of Chinese Academy of Sciences, Beijing, China

    Xiaoming Liu

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  1. Xiaoming Liu
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  2. Hongyu Lin
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  4. Le Sun
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Corresponding authors

Correspondence to Hongyu Lin or Xianpei Han .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Maosong Sun

  2. Harbin Institute of Technology, Harbin, China

    Bing Qin

  3. Fudan University, Shanghai, China

    Xipeng Qiu

  4. School of Computing and Information, Singapore Management University, Singapore, Singapore

    Jiang Jing

  5. Institute of Software, Chinese Academy of Sciences, Beijing, China

    Xianpei Han

  6. Beijing Language and Culture University, Beijing, China

    Gaoqi Rao

  7. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Yubo Chen

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Liu, X., Lin, H., Han, X., Sun, L. (2023). SentBench: Comprehensive Evaluation of Self-Supervised Sentence Representation with Benchmark Construction. In: Sun, M., et al. Chinese Computational Linguistics. CCL 2023. Lecture Notes in Computer Science(), vol 14232. Springer, Singapore. https://doi.org/10.1007/978-981-99-6207-5_28

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  • DOI: https://doi.org/10.1007/978-981-99-6207-5_28

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