3 papers
cs.AI2026
Agent-Orchestration in Autonomous Chip Design
Linyang Li
Recent developments in large language models (LLMs) and tool-using agents encourage people to explore the potential of using agents in chip design. The core question is what kind o…
cs.CV2026
PAVXploreRL: Physical-Action-Visual World Model Reinforcement Learning with Action Exploration
Han Wang, Zijun Wang, Shuoshuo Xue +6
Action-conditioned world models are a key component of embodied AI, serving as scalable policy evaluators that reduce reliance on expensive real-world rollouts. To accurately captu…
cs.CV2026
FactCheck: Feasibility-aware Long-term Action Anticipation with Multi-agent Collaboration
Rui Cao, Jiannong Cao, Bo Yuan +2
Long-term action anticipation (LTA) aims to predict an ordered sequence of future verb-noun actions from a partially observed video. While this task serves as the foundation for em…