7 citations · 8 across the 3 of their papers we have counts for
4 papers
CLAM: Continuous Latent Action Models for Robot Learning from Unlabeled Demonstrations
Anthony Liang, Pavel Czempin, Matthew M. Hong +4
Learning robot control policies from demonstrations typically requires action-labeled expert data, which is expensive to collect through teleoperation. We study a more practical se…
Reducing Exploitability with Population Based Training
Pavel Czempin, Adam Gleave
Self-play reinforcement learning has achieved state-of-the-art, and often superhuman, performance in a variety of zero-sum games. Yet prior work has found that policies that are hi…
Does Audio Deepfake Detection Generalize?
Nicolas M. Müller, Pavel Czempin, Franziska Dieckmann +2
Current text-to-speech algorithms produce realistic fakes of human voices, making deepfake detection a much-needed area of research. While researchers have presented various techni…
Speech is Silver, Silence is Golden: What do ASVspoof-trained Models Really Learn?
Nicolas M. Müller, Franziska Dieckmann, Pavel Czempin +3
We present our analysis of a significant data artifact in the official 2019/2021 ASVspoof Challenge Dataset. We identify an uneven distribution of silence duration in the training…