58 citations · 64 across the 16 of their papers we have counts for
6 papers · 1 filter
APLOT: Robust Reward Modeling via Adaptive Preference Learning with Optimal Transport
Zhuo Li, Yuege Feng, Dandan Guo +3
The reward model (RM) plays a crucial role in aligning Large Language Models (LLMs) with human preferences through Reinforcement Learning, where the Bradley-Terry (BT) objective ha…
Beyond Emotion Recognition: A Multi-Turn Multimodal Emotion Understanding and Reasoning Benchmark
Jinpeng Hu, Hongchang Shi, Chongyuan Dai +3
Multimodal large language models (MLLMs) have been widely applied across various fields due to their powerful perceptual and reasoning capabilities. In the realm of psychology, the…
In-Context Examples Matter: Improving Emotion Recognition in Conversation with Instruction Tuning
Hui Ma, Bo Zhang, Jinpeng Hu +1
Emotion recognition in conversation (ERC) aims to identify the emotion of each utterance in a conversation, playing a vital role in empathetic artificial intelligence. With the gro…
AgentMental: An Interactive Multi-Agent Framework for Explainable and Adaptive Mental Health Assessment
Jinpeng Hu, Ao Wang, Qianqian Xie +3
Mental health assessment is crucial for early intervention and effective treatment, yet traditional clinician-based approaches are limited by the shortage of qualified professional…
Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning
Chongyuan Dai, Jinpeng Hu, Hongchang Shi +4
Amidst a shortage of qualified mental health professionals, the integration of large language models (LLMs) into psychological applications offers a promising way to alleviate the…
Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm
Zhuo Li, Yuhao Du, Xiaoqi Jiao +5
Selecting high-quality and diverse training samples from extensive datasets plays a crucial role in reducing training overhead and enhancing the performance of Large Language Model…