Emotional Support with LLM-based Empathetic Dialogue Generation
Emotional Support Conversation (ESC) aims to provide empathetic and effective emotional assistance through dialogue, addressing the growing demand for mental health support. This paper presents our solution for the NLPCC 2025 Task 8 ESC evaluation, where we leverage large-scale language models enhanced by prompt engineering and finetuning techniques. We explore both parameter-efficient Low-Rank Adaptation and full-parameter fine-tuning strategies to improve the model's ability to generate supportive and contextually appropriate responses. Our best model ranked second in the competition, highlighting the potential of combining LLMs with effective adaptation methods for ESC tasks. Future work will focus on further enhancing emotional understanding and response personalization to build more practical and reliable emotional support systems.
Code (0)
등록된 구현이 없습니다.
Tasks
Dialogue GenerationPrompt EngineeringSimilar Papers 제목 키워드 기반
APTNESS: Incorporating Appraisal Theory and Emotion Support Strategies for Empathetic Response Generation
Empathetic response generation is designed to comprehend the emotions of others and select the most appropriate strategies to assist them in resolving emotional challenges. Empathy can be categorized into cognitive empat…
Empathetic Response GenerationResponse GenerationRetrievalSemantic RetrievalFrom Personas to Talks: Revisiting the Impact of Personas on LLM-Synthesized Emotional Support Conversations
The rapid advancement of Large Language Models (LLMs) has revolutionized the generation of emotional support conversations (ESC), offering scalable solutions with reduced costs and enhanced data privacy. This paper explo…
Knowledge Bridging for Empathetic Dialogue Generation
Lack of external knowledge makes empathetic dialogue systems difficult to perceive implicit emotions and learn emotional interactions from limited dialogue history. To address the above problems, we propose to leverage e…
Dialogue GenerationConstructing Emotional Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation
Researches on dialogue empathy aim to endow an agent with the capacity of accurate understanding and proper responding for emotions. Existing models for empathetic dialogue generation focus on the emotion flow in one dir…
Dialogue GenerationEmpathetic Dialogue Generation with Pre-trained RoBERTa-GPT2 and External Knowledge
One challenge for dialogue agents is to recognize feelings of the conversation partner and respond accordingly. In this work, RoBERTa-GPT2 is proposed for empathetic dialogue generation, where the pre-trained auto-encodi…
DecoderDialogue Generation