Models, methods, and the machinery of intelligence.
arXiv
Verdict: RoutineLong-form agentic video generation must turn a screenplay into shots that remain spatially and temporally consistent across nonconsecutive requests.
Computer-use agents have demonstrated strong capabilities in interpreting screens and executing keyboard and mouse actions.
Scaling interactive environments is important for training long-horizon agents through reinforcement learning.
Long-horizon agents have drawn growing attention for their ability to work autonomously -- from hours to days -- on economically valuable tasks, a capability essential to automated discovery and recursive…
With the rapid development of multimodal large language models (MLLMs), evaluating their video understanding capabilities has become increasingly important.
Visual agents must turn video observations into timely decisions to track progress and choose what to do next.
City-scale 3D grounding is commonly formulated as candidate ranking, which requires precomputed instance proposals and becomes inefficient in large outdoor scenes.
Recent advances in vision-language models (VLMs) have substantially improved the capabilities of GUI agents, while memory augmentation has emerged as a promising approach for reusing ....
Looped Mixture-of-Experts (MoE) models combine parameter reuse with sparse computation to improve performance under matched budgets.