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cs.RO2025
Interpretable Robotic Friction Learning via Symbolic Regression
Philipp Scholl, Alexander Dietrich, Sebastian Wolf +4
Accurately modeling the friction torque in robotic joints has long been challenging due to the request for a robust mathematical description. Traditional model-based approaches are…
cs.LG2025
Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks
Tianyi Zhang, Linrong Cai, Jeffrey Li +4
Weak supervision (WS) is a popular approach for label-efficient learning, leveraging diverse sources of noisy but inexpensive weak labels to automatically annotate training data. D…