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cs.AI2026
PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs
Jiacheng Wang, Weiyan Zhang, Guangya Yu
Enhancing the task-specific capabilities of Large Language Models (LLMs) primarily requires substantial instruction-tuning datasets. However, the sheer volume of such data imposes…
cs.AI2026
PsychÄChat: An Empathic Framework Focused on Emotion Shift Tracking and Safety Risk Analysis in Psychological Counseling
Zhentao Xia, Yongqi Fan, Yuxiang Chu +4
Large language models (LLMs) have demonstrated notable advancements in psychological counseling. However, existing models generally do not explicitly model seekers' emotion shifts…