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20232025
most citedA Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in Conversations

167 citations · 167 across the 1 of their papers we have counts for

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cs.CL2025

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL20234 cited

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…