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Self-supervised Gait-based Emotion Representation Learning from Selective Strongly Augmented Skeleton Sequences
In this paper, we propose a contrastive learning framework utilizing selective strong augmentation (SSA) for self-supervised gait-based emotion representation, which aims to derive effective representations from limited labeled gait data.
Pre-training with Meta Learning for Chinese Word Segmentation
Recent researches show that pre-trained models (PTMs) are beneficial to Chinese Word Segmentation (CWS).
Unified Multi-Criteria Chinese Word Segmentation with BERT
Besides, the pre-trained BERT language model has been also introduced into the MCCWS task in a multi-task learning framework.
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