5 papers
Same Evidence, Different Answers: Canonical-Context On-Policy Distillation for Multi-Turn Language Models
Zizhuo Lin, Quanling Liu, Jinsheng Quan +6
Large language models (LLMs) often solve a task when all instructions are given in a single prompt, but fail when the same information is revealed gradually across turns. When a cl…
DecoupledESC: Enhancing Emotional Support Generation via Strategy-Response Decoupled Preference Optimization
Chao Zhang, Xin Shi, Xueqiao Zhang +3
Recent advances in Emotional Support Conversation (ESC) have improved emotional support generation by fine-tuning Large Language Models (LLMs) via Supervised Fine-Tuning (SFT). How…
Video2Roleplay: A Multimodal Dataset and Framework for Video-Guided Role-playing Agents
Xueqiao Zhang, Chao Zhang, Jingtao Xu +4
Role-playing agents (RPAs) have attracted growing interest for their ability to simulate immersive and interactive characters. However, existing approaches primarily focus on stati…
MASTER: Multi-Agent Security Through Exploration of Roles and Topological Structures -- A Comprehensive Framework
Yifan Zhu, Chao Zhang, Xin Shi +3
Large Language Models (LLMs)-based Multi-Agent Systems (MAS) exhibit remarkable problem-solving and task planning capabilities across diverse domains due to their specialized agent…
EduPlanner: LLM-Based Multi-Agent Systems for Customized and Intelligent Instructional Design
Xueqiao Zhang, Chao Zhang, Jianwen Sun +3
Large Language Models (LLMs) have significantly advanced smart education in the Artificial General Intelligence (AGI) era. A promising application lies in the automatic generalizat…