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cs.RO2026
Optimal Transport Q-Learning for Flow Policy Steering and Acceleration
Andreas Sochopoulos, Esmeralda S. Whitammer, Nikolaos Tsagkas +3
Diffusion and flow policies have recently demonstrated remarkable performance in robotic applications by accurately capturing multimodal robot trajectory distributions, especially…
cs.RO2026
Decoupling the Declarative from the Procedural in Vision-Language-Action Models
Nikolaos Tsagkas, Andreas Sochopoulos, Chris Xiaoxuan Lu +2
Deploying generalist robotic agents in the real world requires transferable skills. Specifically, a policy trained to clone a behavior from object-specific demonstrations must gene…
cs.RO2026
Attentive Feature Aggregation or: How Policies Learn to Stop Worrying about Robustness and Attend to Task-Relevant Visual Cues
Nikolaos Tsagkas, Andreas Sochopoulos, Duolikun Danier +4
The adoption of pre-trained visual representations (PVRs), leveraging features from large-scale vision models, has become a popular paradigm for training visuomotor policies. Howev…