167 citations · 198 across the 6 of their papers we have counts for
6 papers
Efficient Tuning of Large Language Models for Knowledge-Grounded Dialogue Generation
Bo Zhang, Hui Ma, Dailin Li +4
Large language models (LLMs) demonstrate remarkable text comprehension and generation capabilities but often lack the ability to utilize up-to-date or domain-specific knowledge not…
Empathy Level Alignment via Reinforcement Learning for Empathetic Response Generation
Hui Ma, Bo Zhang, Bo Xu +3
Empathetic response generation, aiming to understand the user's situation and feelings and respond empathically, is crucial in building human-like dialogue systems. Traditional app…
PsycoLLM: Enhancing LLM for Psychological Understanding and Evaluation
Jinpeng Hu, Tengteng Dong, Luo Gang +6
Mental health has attracted substantial attention in recent years and LLM can be an effective technology for alleviating this problem owing to its capability in text understanding…
Distilling Implicit Multimodal Knowledge into Large Language Models for Zero-Resource Dialogue Generation
Bo Zhang, Hui Ma, Jian Ding +3
Integrating multimodal knowledge into large language models (LLMs) represents a significant advancement in dialogue generation capabilities. However, the effective incorporation of…
A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in Conversations
Hui Ma, Jian Wang, Hongfei Lin +3
Emotion recognition in conversations (ERC), the task of recognizing the emotion of each utterance in a conversation, is crucial for building empathetic machines. Existing studies f…
ZRIGF: An Innovative Multimodal Framework for Zero-Resource Image-Grounded Dialogue Generation
Bo Zhang, Jian Wang, Hui Ma +2
Image-grounded dialogue systems benefit greatly from integrating visual information, resulting in high-quality response generation. However, current models struggle to effectively…