2 citations · 3 across the 7 of their papers we have counts for
10 papers
Flex-: A Multi-Stream World-Action Model with Compute Flexibility
Ge Yan, Jinghao Liu, Yuzhi Fan +4
World-action models (WAMs) predict the future to act better, but nearly all of them predict only RGB latents, trained purely for pixel reconstruction, with no explicit signal for t…
SeeTraceAct: Visibility-Aware Latent Planning from Cross-Embodiment Demonstration Videos
Jaehyeon Son, Junhyun Kim, Kyle Kam +7
Vision-language-action models (VLAs) are promising general-purpose robot policies, but adapting them to new tasks typically requires costly task-specific teleoperation data. As an…
Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons
Anthony Liang, Yigit Korkmaz, Jiahui Zhang +14
General-purpose robot reward models are typically trained to predict absolute task progress from expert demonstrations, providing only local, frame-level supervision. While effecti…
PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies
Jesse Zhang, Marius Memmel, Kevin Kim +6
Robotic manipulation policies often fail to generalize because they must simultaneously learn where to attend, what actions to take, and how to execute them. We argue that high-lev…
Robot Policy Evaluation for Sim-to-Real Transfer: A Benchmarking Perspective
Xuning Yang, Clemens Eppner, Jonathan Tremblay +3
Current vision-based robotics simulation benchmarks have significantly advanced robotic manipulation research. However, robotics is fundamentally a real-world problem, and evaluati…
GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training
Adithyavairavan Murali, Balakumar Sundaralingam, Yu-Wei Chao +7
Grasping is a fundamental robot skill, yet despite significant research advancements, learning-based 6-DOF grasping approaches are still not turnkey and struggle to generalize acro…
Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control
NVIDIA, :, Hassan Abu Alhaija +38
We introduce Cosmos-Transfer, a conditional world generation model that can generate world simulations based on multiple spatial control inputs of various modalities such as segmen…
HAMSTER: Hierarchical Action Models For Open-World Robot Manipulation
Yi Li, Yuquan Deng, Jesse Zhang +9
Large foundation models have shown strong open-world generalization to complex problems in vision and language, but similar levels of generalization have yet to be achieved in robo…
Aim My Robot: Precision Local Navigation to Any Object
Xiangyun Meng, Xuning Yang, Sanghun Jung +4
Existing navigation systems mostly consider "success" when the robot reaches within 1m radius to a goal. This precision is insufficient for emerging applications where the robot ne…
Open-World Task and Motion Planning via Vision-Language Model Generated Constraints
Nishanth Kumar, William Shen, Fabio Ramos +4
Foundation models like Vision-Language Models (VLMs) excel at common sense vision and language tasks such as visual question answering. However, they cannot yet directly solve comp…