AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 4 of 10 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.
BENCHCOMPASS is introduced, a payment-domain benchmark whose construction pipeline builds scenario-grounded tasks from typed evidence packs, applies LLM-based quality checks, creates task-input attack variants, and reserves final item admission for domain experts.
The proposed ARC (Advantage Regularization via Conditioning), a training recipe that restores fairer relative comparison through strategy-conditioned rollout grouping, together with hybrid rewards and entropy regularization, is proposed.
ACA-RL supports a new mission for NLP evaluation: measuring whether models can recognize when a task is underdetermined and handle uncertainty, not only whether they can answer fully specified questions.
This work proposes \methodname, a stability-guided active-set controller for controlled objective admission, a stability-guided active-set controller for controlled objective admission in reward-vector RLHF, which positions objective-entry timing as a concrete control variable in reward-vector RLHF.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.