2 papers
cs.CV2026
StarWM: Self-Supervised Trained Attention Routing for Robust World Models
Zeqiang Zhang, Fabian Wurzberger, Maximilian Otte +4
A robust world model must strike the balance between faithfully capturing environmental dynamics and abstracting away from irrelevant content. While reconstruction-based world mode…
cs.LG2025
Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback
Zeqiang Zhang, Fabian Wurzberger, Gerrit Schmid +2
Learning from reward functions and imitation learning of demonstrations are the two principal approaches for training autonomous systems that interact with an environment through a…