AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
2 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Imagine-RL is presented, which augments noise-space VLA post-training with action-conditioned visual-torque imagination and improves the average success rate by (23.6%) over DSRL and by (60%) over VLA baselines.
Every valid trajectory can teach what physically happened, while the actor is deployed only under the condition associated with relatively better actions, in \method, a direct world-action policy that combines outcome-agnostic predictive learning with outcome-aware policy improvement.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.