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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 10: AAAI-22 Technical Tracks 10

Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives

February 1, 2023

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Authors

Yanzhao Zhang

Beihang University


Richong Zhang

Beihang University


Samuel Mensah

University of Sheffield


Xudong Liu

Beihang University


Yongyi Mao

University of Ottawa


DOI:

10.1609/aaai.v36i10.21428


Abstract:

Unsupervised sentence representation learning is a fundamental problem in natural language processing. Recently, contrastive learning has made great success on this task. Existing constrastive learning based models usually apply random sampling to select negative examples for training. Previous work in computer vision has shown that hard negative examples help contrastive learning to achieve faster convergency and better optimization for representation learning. However, the importance of hard negatives in contrastive learning for sentence representation is yet to be explored. In this study, we prove that hard negatives are essential for maintaining strong gradient signals in the training process while random sampling negative examples is ineffective for sentence representation. Accordingly, we present a contrastive model, MixCSE, that extends the current state-of-the-art SimCSE by continually constructing hard negatives via mixing both positive and negative features. The superior performance of the proposed approach is demonstrated via empirical studies on Semantic Textual Similarity datasets and Transfer task datasets.

Topics: AAAI

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HOW TO CITE:

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives Proceedings of the AAAI Conference on Artificial Intelligence (2022) 11730-11738.

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives AAAI 2022, 11730-11738.

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao (2022). Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives. Proceedings of the AAAI Conference on Artificial Intelligence, 11730-11738.

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao. Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.11730-11738.

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao. 2022. Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives. "Proceedings of the AAAI Conference on Artificial Intelligence". 11730-11738.

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao. (2022) "Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives", Proceedings of the AAAI Conference on Artificial Intelligence, p.11730-11738

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao, "Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives", AAAI, p.11730-11738, 2022.

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao. "Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.11730-11738.

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao. "Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 11730-11738.

Yanzhao Zhang||Richong Zhang||Samuel Mensah||Xudong Liu||Yongyi Mao. Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives. AAAI[Internet]. 2022[cited 2023]; 11730-11738.


ISSN: 2374-3468


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Copyright 2022, Association for the Advancement of
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