118 citations · 459 across the 29 of their papers we have counts for
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Temporal Difference Calibration in Sequential Tasks: Application to Vision-Language-Action Models
Shelly Francis-Meretzki, Mirco Mutti, Yaniv Romano +1
Recent advances in vision-language-action (VLA) models for robotics have highlighted the importance of reliable uncertainty quantification in sequential tasks. However, assessing a…
Blindfolded Experts Generalize Better: Insights from Robotic Manipulation and Videogames
Ev Zisselman, Mirco Mutti, Shelly Francis-Meretzki +2
Behavioral cloning is a simple yet effective technique for learning sequential decision-making from demonstrations. Recently, it has gained prominence as the core of foundation mod…
From Configuration-Space Clearance to Feature-Space Margin: Sample Complexity in Learning-Based Collision Detection
Sapir Tubul, Aviv Tamar, Kiril Solovey +1
Motion planning is a central challenge in robotics, with learning-based approaches gaining significant attention in recent years. Our work focuses on a specific aspect of these app…
RoboArm-NMP: a Learning Environment for Neural Motion Planning
Tom Jurgenson, Matan Sudry, Gal Avineri +1
We present RoboArm-NMP, a learning and evaluation environment that allows simple and thorough evaluations of Neural Motion Planning (NMP) algorithms, focused on robotic manipulator…
Entity-Centric Reinforcement Learning for Object Manipulation from Pixels
Dan Haramati, Tal Daniel, Aviv Tamar
Manipulating objects is a hallmark of human intelligence, and an important task in domains such as robotics. In principle, Reinforcement Learning (RL) offers a general approach to…
Efficient Self-Supervised Data Collection for Offline Robot Learning
Shadi Endrawis, Gal Leibovich, Guy Jacob +2
A practical approach to robot reinforcement learning is to first collect a large batch of real or simulated robot interaction data, using some data collection policy, and then lear…