1 citations · 1 across the 24 of their papers we have counts for
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Thinking with Images without Coordinates
Meng Cao, Haoze Zhao, Yi Wang +2
Recent advances in multi-modal large language models have shifted toward the "thinking with images" paradigm to improve reasoning faithfulness, yet existing methods rely heavily on…
Mr.LHDR: A Benchmark for Multimodal Real-World Long-Horizon Deep Research Agents
Minghao Guo, Meng Cao, Sui Zhao +10
Deep research agents are increasingly capable of web search, tool use, multimodal evidence analysis, and information synthesis. However, existing benchmarks mainly evaluate medium-…
PAVXploreRL: Physical-Action-Visual World Model Reinforcement Learning with Action Exploration
Han Wang, Zijun Wang, Shuoshuo Xue +5
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…
STEAM: Self-Supervised Temporal Ensemble Advantage Modeling for Real-World Robot Learning
Zhihao Liu, Qiuyi Gu, Yitao Wang +16
Real-world robot learning increasingly relies on heterogeneous data, but demonstrations and rollouts often mix useful progress with stalls, corrections, and suboptimal behavior. Ef…
AnyCrowd: Instance-Isolated Identity-Pose Binding for Arbitrary Multi-Character Animation
Zhenyu Xie, Ji Xia, Michael Kampffmeyer +9
Controllable character animation has advanced rapidly in recent years, yet multi-character animation remains underexplored. As the number of characters grows, multi-character refer…
World2Act: Latent Action Post-Training from World Model Dynamics
An Dinh Vuong, Tuan Van Vo, Abdullah Sohail +6
World Models (WMs) offer a promising mechanism for post-training Vision-Language-Action (VLA) policies by providing dynamics priors that improve generalization under task and scene…
Order from Chaos: Physical World Understanding from Glitchy Gameplay Videos
Meng Cao, Haoran Tang, Haoze Zhao +6
Understanding the physical world, including object dynamics, material properties, and causal interactions, remains a core challenge in artificial intelligence. Although recent mult…
Training and Benchmarking Code Generation for Physics-Inspired Animations
Yanan Wang, Renxi Wang, Yongxin Wang +5
Large language models (LLMs) have been widely studied in areas such as mathematical reasoning, complex coding, and scientific problem solving. However, their ability to generate ex…