Few-shot intent detection with self-supervised pretraining and prototype-aware attention

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Few-shot multi-label intent recognition augmented by label knowledge generalization method

ZY Li, YJ Du, S Yang, XL Chen, XY Li - Information Fusion, 2025 - Elsevier
Recognizing user intents is one of the most critical aspects of human–computer interaction.
However, most research typically assumes a single intent, whereas real-world user …
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Few-shot cyberviolence intent classification with Meta-learning AutoEncoder based on adversarial domain adaptation

S Yang, YJ Du, SY Du, XY Li, XL Chen, YL Li, CZ **e… - Neurocomputing, 2025 - Elsevier
The phenomenon of cyberviolence has become a critical issue in online security, drawing
attention from various stakeholders. A major shortcoming in the previous works is the …
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Few-shot intent detection with mutual information and contrastive learning

S Yang, YJ Du, JM Huang, XY Li, SY Du, J Liu… - Applied Soft …, 2024 - Elsevier
Few-shot intent detection is a challenging task. Most existing methods only focus on
acquisition of generalization knowledge in known classes, or on the adaptation situation of …
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