Papers by Liangjun Zang
Text Smoothing: Enhance Various Data Augmentation Methods on Text Classification Tasks (2022.acl-short)
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| Challenge: | Experimental results show text smoothing outperforms data augmentation methods by a substantial margin. |
| Approach: | They propose to use a masked language model to convert a token to a smoothed representation by converting a sentence from its one-hot representation to 'controllable smoothes' they propose to combine text smoothing with other data augmentation methods to achieve better performance. |
| Outcome: | The proposed method outperforms mainstream data augmentation methods by a substantial margin on different datasets in a low-resource regime. |
ESimCSE: Enhanced Sample Building Method for Contrastive Learning of Unsupervised Sentence Embedding (2022.coling-1)
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| Challenge: | a new method for learning unsupervised sentence embeddings is proposed . unsup-SimCSE is biased because of the length information encoded into the sentence embeds . |
| Approach: | They propose a new unsupervised sentence embedding method that uses dropout to obtain positive pairs from a pre-trained Transformer encoder. |
| Outcome: | The proposed method outperforms the state-of-the-art unsup-SimCSE on a STS task. |