We have 5 of 15 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Meta-TTL is introduced, a framework that formulates the discovery of effective self-improvement policies as a bi-level optimization problem and consistently outperforms existing baselines, suggesting that the optimized self-improvement policy encodes transferable meta-strategies that generalize beyond the training task...
Within this trained-task regime, DEM sits on the observed success--latency--energy frontier and provides a strong, efficient baseline for language-conditioned robot skills.
Sampling-Guided Policy Search (SGPS), which couples recurring action-target refinement by sampling-based model-predictive control with first-order policy optimization with first-order policy optimization, and shows that refinement improves policy learning beyond initialization and tracking alone.
WALL-SS is introduced, a world model that generates visual futures through Scale-wise autoregressive Scaling, enabling action-controllable and long-horizon robotic simulation, and consistently benefits from on-policy alignment in reducing action drift and long-horizon inconsistency.
Artificial Foveated Perception is proposed, a lightweight, policy-agnostic module that takes the same vision and language inputs as Vision-Language-Action and World Action Model pipelines and predicts task-conditioned masks over relevant objects, the robot, and other action-critical regions and reduces fine-tuning time...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
