Manipulation, locomotion, sim-to-real transfer and autonomous driving: learning systems that have to survive physics.
arXiv:2609.33965v2 Announce Type: replace-cross Abstract: We describe a methodology for estimating the per-token energy cost of cloud-hosted large language model (LLM) inference, separating between i...
arXiv:2609.36691v1 Announce Type: new Abstract: Manipulation behaviors vary widely across objects and scenes, but they share a small set of reusable skills, and planning with these skills helps embod...
arXiv:2609.35916v1 Announce Type: cross Abstract: Real-world embodied agents often pursue independent objectives within a shared physical environment, where their actions can alter the conditions fac...
arXiv:2609.37476v1 Announce Type: cross Abstract: Training robust social-navigation policies requires simulators with diverse scene layouts, terrain, and human motion, but constructing such environme...
arXiv:2609.35823v1 Announce Type: new Abstract: Vision-language models (VLMs) have made substantial progress in autonomous driving, but their success has primarily been studied in ego-centric scenes....
arXiv:2609.36454v1 Announce Type: new Abstract: We study hand-object interaction (HOI) reconstruction from monocular RGB videos, where partial observations can produce visually plausible yet mechanic...
arXiv:2609.36755v1 Announce Type: new Abstract: Modern image editors excel at semantic manipulation and visual synthesis, yet remain limited in precise spatial control, motivating the development of...
arXiv:2609.36801v1 Announce Type: new Abstract: Interactive simulations of embodied AI or spatial computing applications build on realistic 3D scenes that support daily activities. However, sparse, i...
arXiv:2609.36844v1 Announce Type: new Abstract: Transparent surfaces are ubiquitous in built environments, yet they remain a persistent failure case for robotic perception. RGB cameras perceive the b...
arXiv:2609.37089v1 Announce Type: new Abstract: Real-world videos provide rich demonstrations of manipulation, but turning them into reusable robot skills requires visually aligned environments, exec...
arXiv:2609.37135v1 Announce Type: new Abstract: Using language instructions as conditions to guide robot policy learning has recently become an important research domain. However, existing language-g...
arXiv:2609.37495v1 Announce Type: new Abstract: Human motion generation plays an important role in applications such as character animation, virtual environments, and embodied interaction. While exis...
arXiv:2609.37655v1 Announce Type: new Abstract: Advancing spatial intelligence in Multimodal Large Language Models (MLLMs) is bottlenecked by the scarcity of complex, scalable 3D question-answer (QA)...
arXiv:2609.37870v1 Announce Type: new Abstract: Raindrops adhered to camera lens or windshield are inevitable in rainy scenes and can become an issue for many computer vision systems such as autonomo...
arXiv:2609.38057v1 Announce Type: new Abstract: Improving robot policies on new tasks without collecting additional expert demonstrations remains a central challenge in robot learning. World action m...
arXiv:2609.38163v1 Announce Type: new Abstract: World-action models jointly learn robot policies and predict future observations, making the representation space an interface between control and pred...
arXiv:2609.36520v1 Announce Type: cross Abstract: RGB-only end-to-end visual navigation policies remain vulnerable to collisions in real-world dynamic environments, motivating a dedicated safety laye...
arXiv:2609.36779v1 Announce Type: cross Abstract: Accurate hand-eye calibration is crucial for precision manipulation. Traditional methods rely on markers, with their precision dependent on marker ac...
arXiv:2609.37602v1 Announce Type: cross Abstract: Robust and reliable perception is essential for autonomous robots operating in real-world environments, particularly in long-term missions where envi...
arXiv:2609.38059v1 Announce Type: cross Abstract: Real-world robot learning is constrained by the cost of collecting experience and evaluating candidate behaviors. Video generation models offer a sca...