From the 1 of 8 linked papers with an AI index.
8 papers
RoboWorld: Fast and Reliable Neural Simulators for Generalist Robot Policy Evaluation
Byeongguk Jeon, Seonghyeon Ye, JaeHyeok Doo +4
RoboWorld is an automated pipeline that uses a fast autoregressive video world model and a vision-language scoring system to evaluate generalist robot policies efficiently and reli…
Beyond Monotonic Progress: Retry-Supervised Value Learning for Robot Imitation
Xinyao Qin, Junjie Lu, Kaixin Wang +7
Human demonstrations for robot imitation learning often contain mistakes and corrective behaviors, such as imprecise grasps, object misalignment, unstable contact, and repeated att…
HABIT: Human-Aware Behavior and Interaction Training Dataset for Robot Manipulation
Jaehwi Song, Suchae Jeong, Byeongguk Jeon +4
Large-scale demonstration datasets have been central to recent progress in general-purpose robot policies. However, existing datasets are collected in human-absent settings, and po…
SPACE: Enabling Learning from Cross-Robot Data Toward Generalist Policies
Haeone Lee, Byeongguk Jeon, Suchae Jeong +2
In robot learning, scaling training datasets across diverse embodiments and environments has become a dominant paradigm for learning generalizable robot policies. These policies ar…
Q-Flow: Stable and Expressive Reinforcement Learning with Flow-Based Policy
JaeHyeok Doo, Byeongguk Jeon, Seonghyeon Ye +2
There is growing interest in utilizing flow-based models as decision-making policies in reinforcement learning due to their high expressive capacity. However, effectively leveragin…
WarmPrior: Straightening Flow-Matching Policies with Temporal Priors
Sinjae Kang, Chanyoung Kim, Kaixin Wang +2
Generative policies based on diffusion and flow matching have become a dominant paradigm for visuomotor robotic control. We show that replacing the standard Gaussian source distrib…