7 papers
Mean-Field Diffuser: Scaling Offline MARL to Thousands of Agents
Wenhao Li, Xiangfeng Wang, Bo Jin
Diffusion-based planning has achieved strong results in single-agent offline reinforcement learning, yet scaling to many-agent systems remains intractable due to the curse of dimen…
Unifying Temporal and Structural Credit Assignment in LLM-Based Multi-Agent Prompt Optimization
Wenwu Li, Yuran Song, Mingze Zhao +2
While Multi-Agent Systems (MAS) empower Large Language Models to tackle complex reasoning tasks through collaborative interaction, optimizing their dynamics remains a formidable ch…
Interpretable Hybrid-Rule Temporal Point Processes
Yunyang Cao, Juekai Lin, Hongye Wang +2
Temporal Point Processes (TPPs) are widely used for modeling event sequences in various medical domains, such as disease onset prediction, progression analysis, and clinical decisi…
Leveraging Vision-Language Large Models for Interpretable Video Action Recognition with Semantic Tokenization
Jingwei Peng, Zhixuan Qiu, Boyu Jin +1
Human action recognition often struggles with deep semantic understanding, complex contextual information, and fine-grained distinction, limitations that traditional methods freque…
MOCHA: Discovering Multi-Order Dynamic Causality in Temporal Point Processes
Yunyang Cao, Juekai Lin, Wenhao Li +1
Discovering complex causal dependencies in temporal point processes (TPPs) is critical for modeling real-world event sequences. Existing methods typically rely on static or first-o…
Reinforced Reasoning for Embodied Planning
Di Wu, Jiaxin Fan, Junzhe Zang +4
Embodied planning requires agents to make coherent multi-step decisions based on dynamic visual observations and natural language goals. While recent vision-language models (VLMs)…