Multi Role
"Multi-role" research explores how large language models (LLMs) and other AI systems can effectively perform multiple functions or adopt diverse perspectives within a single application. Current research focuses on improving LLMs' ability to maintain consistent roles in complex scenarios (e.g., role-playing, collaborative learning), mitigating issues like character hallucination and ensuring adherence to predefined rules. This work is significant for advancing AI capabilities in various fields, including education, combating misinformation, and improving human-computer interaction, by enabling more nuanced and adaptable AI systems.
Papers
Multi-role Consensus through LLMs Discussions for Vulnerability Detection
Zhenyu Mao, Jialong Li, Dongming Jin, Munan Li, Kenji Tei
PeerGPT: Probing the Roles of LLM-based Peer Agents as Team Moderators and Participants in Children's Collaborative Learning
Jiawen Liu, Yuanyuan Yao, Pengcheng An, Qi Wang
On the Roles of LLMs in Planning: Embedding LLMs into Planning Graphs
Hankz Hankui Zhuo, Xin Chen, Rong Pan
Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction
Yinghui Li, Shang Qin, Haojing Huang, Yangning Li, Libo Qin, Xuming Hu, Wenhao Jiang, Hai-Tao Zheng, Philip S. Yu