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Yuzhe Zi

3 accepted papers

2025

Balancing Forget Quality and Model Utility: A Reverse KL-Divergence Knowledge Distillation Approach for Better Unlearning in LLMs

NAACL 2025long

As concern for privacy rights has grown and the size of language model training datasets has expanded, research into machine unlearning for large language models (LLMs) has become crucial. Before the era of LLMs, research on machine unlearning mainly focused on classification tasks in small paramete…

2025

End-to-End Learnable Psychiatric Scale Guided Risky Post Screening for Depression Detection on Social Media

EMNLP 2025

Detecting depression through users’ social media posting history is crucial for enabling timely intervention; however, irrelevant content within these posts negatively impacts detection performance. Thus, it is crucial to extract pertinent content from users’ complex posting history. Current methods

Cited by 0SourcePDFScholar
2024

ESDM: Early Sensing Depression Model in Social Media Streams

COLING 2024main

Depression impacts millions worldwide, with increasing efforts to use social media data for early detection and intervention. Traditional Risk Detection (TRD) uses a user’s complete posting history for predictions, while Early Risk Detection (ERD) seeks early detection in a user’s posting history, e…