Papers with unsupervised learning models

1 papers
Unsupervised Extractive Summarization of Emotion Triggers (2023.acl-long)

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Challenge: Recent approaches trained supervised models to detect emotions and explain emotion triggers via abstractive summarization, but this can block necessary responses.
Approach: They propose to augment an abstractive dataset with extractive triggers and develop unsupervised models that can jointly detect emotions and summarize their triggers.
Outcome: The proposed model outperforms existing models and is based on a COVID-19 crisis dataset.

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