3 citations · 3 across the 4 of their papers we have counts for
5 papers
Scaling Latent Motor Adaptation to Coordinated Bimanual Manipulation
Seung-Bin Joo, Alessandro Albini, Luca Wiehe +3
Robust manipulation under uncertain object dynamics and geometry remains a core challenge in real-world robotics. Policies trained under fixed assumptions often degrade when object…
AI Research Preference Models
Thomas Simon Foster, Bassel Al Omari, Tingchen Fu +30
AI research agents (AIRA) can now carry machine learning experiments from proposal through implementation and evaluation. Yet progress on frontier tasks is throttled by the cost of…
Finding the Time to Think: Learning Planning Budgets in Real-Time RL
Aneesh Muppidi, Firas Darwish, Dylan Cope +2
Deliberating takes time. In real-time settings, that time is not free. Standard reinforcement learning (RL) sidesteps this as the environment waits indefinitely for the agent's dec…
VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning
Yichao Liang, Nishanth Kumar, Hao Tang +5
Broadly intelligent agents should form task-specific abstractions that selectively expose the essential elements of a task, while abstracting away the complexity of the raw sensori…
Rapid Motor Adaptation for Robotic Manipulator Arms
Yichao Liang, Kevin Ellis, João Henriques
Developing generalizable manipulation skills is a core challenge in embodied AI. This includes generalization across diverse task configurations, encompassing variations in object…