摘要
大语言模型因其出色的情景学习和因果推理能力已越来越多地应用于人们的生活中,与大语言模型能力相对应的是在社区矛盾调解中需调解员在了解完矛盾纠纷后,对是非有一定的辨别能力,并站在中立角度对矛盾进行调解。大语言模型可以在一定程度上缓解现有的社区矛盾调解制度中存在的人力资源不足、调解难度高、公信力缺失的问题,但大语言模型昂贵的调用费用,又限制了其在基层社区中的使用。鉴于此,提出一种基于大小语言模型协同的社区矛盾调解框架,该框架使用免费的小语言模型生成矛盾摘要,并根据调解员的参与方式分为人机分流与人机协同。案例分析表明,该框架可以将调用大语言模型带来的花费降低到原本的一半以下,且调解质量趋向于人工调解员。
The large language models(LLM)are increasingly being applied in people′s lives due to their remarkable ability in contextual learning and causal reasoning.Corresponding to the capabilities of LLM,mediators in community conflict resolution require a certain level of discernment and a neutral perspective to mediate conflicts after understanding them thoroughly.Therefore,LLM can to some extent alleviate the issues of insufficient human resources,high mediation difficulty,and lack of credibility in existing community conflict resolution systems.However,the cost of invoking LLM limits their usage in communities.This paper proposes a framework based on the collaboration between large and small language models.The framework utilizes freely available small language models to generate conflict summaries and is divided into two approaches:human-machine diversion and human-machine collaboration,based on the mediator′s level of involvement.Experiments demonstrate that this framework can reduce the cost while approaching the mediation quality provided by human mediators.
作者
陈董
王曼
戴光裕
张硕
汤斯亮
庄越挺
CHEN Dong;WANG Man;DAI Guangyu;ZHANG Shuo;TANG Siiang;ZHUANG Yueting(School of Computer and Artificial Intelligence,School of Software,Zhengzhou University,Zhengzhou 450066,China;School of Chinese International Education,Hangzhou Normal University,Hangzhou 311121,China;College of Computer Science and Technolo-gy,Zhejiang University,Hangzhou 310013,China;School of Software Engineering,Zhejiang University,Ningbo 315048,China)
出处
《软件导刊》
2024年第7期40-44,共5页
Software Guide
基金
国家自然科学基金项目(62272411)
浙江省杰出青年基金项目(LR21F020004)。
关键词
大语言模型
小语言模型
人机分流
人机协同
矛盾调解
large language model
small language model
human-machine separation
human-machine collaboration
conflict resolution
