Papers by Peixiang Zhong
Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations (D19-1)
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| Challenge: | Existing methods to analyze emotions in textual conversations are limited . emotion detection is challenging because humans rely on context and commonsense knowledge to express emotions . |
| Approach: | They propose a Knowledge-Enriched Transformer where contextual utterances are interpreted using hierarchical self-attention and external commonsense knowledge is dynamically leveraged. |
| Outcome: | The proposed model outperforms state-of-the-art models on most of the tested datasets in F1 score. |
Towards Persona-Based Empathetic Conversational Models (2020.emnlp-main)
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| Challenge: | Empathetic conversational models have been shown to improve user satisfaction and task outcomes in numerous domains. |
| Approach: | They propose a task towards persona-based empathetic conversations and propose e-learning model CoBERT that can be used to train persona on emmpathetic conversations. |
| Outcome: | The proposed model improves empathetic responding more when trained on e-mpathetic conversations than non-empathy ones. |