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

SAS: Self-Augmentation Strategy for Language Model Pre-training

February 1, 2023

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Authors

Yifei Xu

University of California, Los Angeles


Jingqiao Zhang

Alibaba Group


Ru He

Alibaba Group


Liangzhu Ge

Alibaba Group


Chao Yang

Alibaba Group


Cheng Yang

Alibaba Group


Ying Nian Wu

University of California, Los Angeles


DOI:

10.1609/aaai.v36i10.21412


Abstract:

The core of self-supervised learning for pre-training language models includes pre-training task design as well as appropriate data augmentation. Most data augmentations in language model pre-training are context-independent. A seminal contextualized augmentation was recently proposed in ELECTRA and achieved state-of-the-art performance by introducing an auxiliary generation network (generator) to produce contextualized data augmentation for the training of a main discrimination network (discriminator). This design, however, introduces extra computation cost of the generator and a need to adjust the relative capability between the generator and the discriminator. In this paper, we propose a self-augmentation strategy (SAS) where a single network is utilized for both regular pre-training and contextualized data augmentation for the training in later epochs. Essentially, this strategy eliminates a separate generator and uses the single network to jointly conduct two pre-training tasks with MLM (Masked Language Modeling) and RTD (Replaced Token Detection) heads. It avoids the challenge to search for an appropriate size of the generator, which is critical to the performance as evidenced in ELECTRA and its subsequent variant models. In addition, SAS is a general strategy that can be seamlessly combined with many new techniques emerging recently or in the future, such as the disentangled attention mechanism from DeBERTa. Our experiments show that SAS is able to outperform ELECTRA and other state-of-the-art models in the GLUE tasks with similar or less computation cost.

Topics: AAAI

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HOW TO CITE:

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu SAS: Self-Augmentation Strategy for Language Model Pre-training Proceedings of the AAAI Conference on Artificial Intelligence (2022) 11586-11594.

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu SAS: Self-Augmentation Strategy for Language Model Pre-training AAAI 2022, 11586-11594.

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu (2022). SAS: Self-Augmentation Strategy for Language Model Pre-training. Proceedings of the AAAI Conference on Artificial Intelligence, 11586-11594.

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu. SAS: Self-Augmentation Strategy for Language Model Pre-training. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.11586-11594.

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu. 2022. SAS: Self-Augmentation Strategy for Language Model Pre-training. "Proceedings of the AAAI Conference on Artificial Intelligence". 11586-11594.

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu. (2022) "SAS: Self-Augmentation Strategy for Language Model Pre-training", Proceedings of the AAAI Conference on Artificial Intelligence, p.11586-11594

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu, "SAS: Self-Augmentation Strategy for Language Model Pre-training", AAAI, p.11586-11594, 2022.

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu. "SAS: Self-Augmentation Strategy for Language Model Pre-training". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.11586-11594.

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu. "SAS: Self-Augmentation Strategy for Language Model Pre-training". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 11586-11594.

Yifei Xu||Jingqiao Zhang||Ru He||Liangzhu Ge||Chao Yang||Cheng Yang||Ying Nian Wu. SAS: Self-Augmentation Strategy for Language Model Pre-training. AAAI[Internet]. 2022[cited 2023]; 11586-11594.


ISSN: 2374-3468


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