We have 2 of 5 papers
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.
CANOPY, a multi-fidelity tree bandit that learns where the smoothness prior is valid rather than assuming it globally, is introduced, a multi-fidelity tree bandit that consistently improves matched-budget performance.
Noise-Contrastive GRPO is introduced, which injects scale-calibrated Gaussian noise into the last hidden layer of the prompt-encoding pass for half of each rollout group, branching those rollouts from a displaced departure state and integrates into a standard RLVR pipeline as a ~50-line change to the inference engine.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
