6 papers
World Models for Policy Refinement in StarCraft II
Yixin Zhang, Ziyi Wang, Yiming Rong +6
Large Language Models (LLMs) have recently shown strong reasoning and generalization capabilities, motivating their use as decision-making policies in complex environments. StarCra…
MrCoM: A Meta-Regularized World-Model Generalizing Across Multi-Scenarios
Xuantang Xiong, Ni Mu, Runpeng Xie +8
Model-based reinforcement learning (MBRL) is a crucial approach to enhance the generalization capabilities and improve the sample efficiency of RL algorithms. However, current MBRL…
DAIL: Beyond Task Ambiguity for Language-Conditioned Reinforcement Learning
Runpeng Xie, Quanwei Wang, Hao Hu +7
Comprehending natural language and following human instructions are critical capabilities for intelligent agents. However, the flexibility of linguistic instructions induces substa…
SC2Arena and StarEvolve: Benchmark and Self-Improvement Framework for LLMs in Complex Decision-Making Tasks
Pengbo Shen, Yaqing Wang, Ni Mu +8
Evaluating large language models (LLMs) in complex decision-making is essential for advancing AI's ability for strategic planning and real-time adaptation. However, existing benchm…
DPMT: Dual Process Multi-scale Theory of Mind Framework for Real-time Human-AI Collaboration
Xiyun Li, Yining Ding, Yuhua Jiang +6
Real-time human-artificial intelligence (AI) collaboration is crucial yet challenging, especially when AI agents must adapt to diverse and unseen human behaviors in dynamic scenari…
LVC: A Lightweight Compression Framework for Enhancing VLMs in Long Video Understanding
Ziyi Wang, Haoran Wu, Yiming Rong +5
Long video understanding is a complex task that requires both spatial detail and temporal awareness. While Vision-Language Models (VLMs) obtain frame-level understanding capabiliti…