Papers by Guanghui Fu

3 papers
Generalizable Cross-Lingual Cognitive Distortion Detection with Standardized Annotations and Multi-Task Learning (2025.findings-acl)

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Challenge: Existing studies on cognitive distortion have limited generalizability and performance of models in large-scale and cross-linguistic contexts.
Approach: They propose a multi-task learning model based on teacher student architecture solution which improves generalization performance.
Outcome: The proposed model improves generalizability and interpretability of the proposed model.
MentalGLM Series: Explainable Large Language Models for Mental Health Analysis on Chinese Social Media (2025.emnlp-main)

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Challenge: Social media is a key platform for emotional expression, yet deep learning lacks flexibility and interpretability.
Approach: They propose to use Chinese social media to train interpretable mental health instruction datasets to test models' ability to explain their decisions.
Outcome: The proposed models outperform deep learning and LLMs on three mental health downstream tasks and demonstrate their potential for clinical applications.
Chinese MentalBERT: Domain-Adaptive Pre-training on Social Media for Chinese Mental Health Text Analysis (2024.findings-acl)

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Challenge: Existing models for language analysis are inadequate for specialized domains like psychology.
Approach: They have enriched a Chinese social media database with psychological lexicons to enhance its applicability to psychological text analysis.
Outcome: The proposed model performed better on six public datasets and provided relevant predictions given the masked sentences.

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