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20122025
most citedSocratic Models: Composing Zero-Shot Multimodal Reasoning with Language

173 citations · 876 across the 56 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

cs.RO2023★ 1 cited

SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention

Isabel Leal, Krzysztof Choromanski, Deepali Jain +11

We present Self-Adaptive Robust Attention for Robotics Transformers (SARA-RT): a new paradigm for addressing the emerging challenge of scaling up Robotics Transformers (RT) for on-…

cs.RO2023★ 2 cited

Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models

Sumeet Singh, Stephen Tu, Vikas Sindhwani

A crucial design decision for any robot learning pipeline is the choice of policy representation: what type of model should be used to generate the next set of robot actions? Owing…

cs.RO2023★ 18 cited

Robotic Table Tennis: A Case Study into a High Speed Learning System

David B. D'Ambrosio, Jonathan Abelian, Saminda Abeyruwan +32

We present a deep-dive into a real-world robotic learning system that, in previous work, was shown to be capable of hundreds of table tennis rallies with a human and has the abilit…

cs.RO2023★ 2 cited

Agile Catching with Whole-Body MPC and Blackbox Policy Learning

Saminda Abeyruwan, Alex Bewley, Nicholas M. Boffi +9

We address a benchmark task in agile robotics: catching objects thrown at high-speed. This is a challenging task that involves tracking, intercepting, and cradling a thrown object…

cs.RO2023★ 13 cited

Barkour: Benchmarking Animal-level Agility with Quadruped Robots

Ken Caluwaerts, Atil Iscen, J. Chase Kew +41

Animals have evolved various agile locomotion strategies, such as sprinting, leaping, and jumping. There is a growing interest in developing legged robots that move like their biol…

math.OC2023★ 1 cited

Safely Learning Dynamical Systems

Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani +1

A fundamental challenge in learning an unknown dynamical system is to reduce model uncertainty by making measurements while maintaining safety. We formulate a mathematical definiti…