284 citations · 822 across the 48 of their papers we have counts for
50 papers
Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning
Ismail Geles, Leonard Bauersfeld, Markus Wulfmeier +1
Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, dynamic real-world spaces. This failure stems from the domina…
What Matters for Simulation to Online Reinforcement Learning on Real Robots
Yarden As, Dhruva Tirumala, René Zurbrügg +4
We investigate what specific design choices enable successful online reinforcement learning (RL) on physical robots. Across 100 real-world training runs on three distinct robotic p…
Improving cosmological reach of a gravitational wave observatory using Deep Loop Shaping
Jonas Buchli, Brendan Tracey, Tomislav Andric +28
Improved low-frequency sensitivity of gravitational wave observatories would unlock study of intermediate-mass black hole mergers, binary black hole eccentricity, and provide early…
Exploiting Policy Idling for Dexterous Manipulation
Annie S. Chen, Philemon Brakel, Antonia Bronars +7
Learning-based methods for dexterous manipulation have made notable progress in recent years. However, learned policies often still lack reliability and exhibit limited robustness…
Cognitive models can reveal interpretable value trade-offs in language models
Sonia K. Murthy, Rosie Zhao, Jennifer Hu +4
Value trade-offs are an integral part of human decision-making and language use, however, current tools for interpreting such dynamic and multi-faceted notions of values in languag…
Position: The ML Community Must Build an AI-Augmented Peer-Review Ecosystem
Qiyao Wei, Samuel Holt, Jing Yang +2
Peer review, the bedrock of scientific advancement in machine learning (ML), is strained by a crisis of scale. Exponential growth in manuscript submissions to premier ML venues suc…