Jie Gui

GPT-Policy is introduced, a general-agent framework for in-context robot learning that integrates a context compiler that preserves task-relevant visual transitions, a VLM that proposes robot-tool actions, and a constrained controller that verifies and executes each action and reports its outcome.

Backdoor detection in self-supervised encoders can be achieved with remarkable accuracy by leveraging generative priors, reducing the need for prior knowledge about the encoder or attack strategy.