Papers by Daejin Choi
CURE: Context- and Uncertainty-Aware Mental Disorder Detection (2024.emnlp-main)
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| Challenge: | Existing methods to detect mental disorders focus on the presence of symptoms, but the context of symptoms is often ignored, leading to errors in symptom identification. |
| Approach: | They propose to use large language models to extract contextual information while introducing an uncertainty-aware decision fusion network that combines predictions of multiple models based on quantified uncertainty values. |
| Outcome: | The proposed model detects mental disorders even in situations where symptom information is incomplete. |
Cross-Lingual Suicidal-Oriented Word Embedding toward Suicide Prevention (2020.findings-emnlp)
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| Challenge: | Existing suicide dictionaries for other languages have been limited to Korean . a model that uses social media data to identify whether a post includes suicidal ideation is useful . |
| Approach: | They propose a model that uses existing suicide dictionaries for Korean to predict suicidal ideation . they use the existing dictionary for English and Chinese to translate a post into English and then use the separate suicide-oriented embeddings for English. |
| Outcome: | The proposed model can detect whether a given social media post includes suicidal ideation in Korean . it uses existing suicide dictionaries for other languages to translate the post into English and Chinese, and then embeds the suicide-oriented embeddings for English and China. |