AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 4 of 22 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.
Princigram shows that explicit physics-structured supervision improves the physical faithfulness of generated scientific diagrams, and curate and structurally annotate 4.3 million physics images, carry expert-level annotation, and adapt a unified multimodal backbone.
SIVA-RL is proposed, a Sensitivity-Invariance Visual Alignment framework that replaces operator-conditioned regularization with sample-wise, outcome-conditioned supervision and yields an 8.79 percentage-point gain on vision-dependent reasoning and up to 14.9% relative overall improvement across all four GRPO- and DAPO-...
Claim-level falsification is proposed as a principle for test-time scaling and instantiated through Claim-Level Reliability Assessment (CLR), a training-free framework that reallocates test-time compute from additional solution sampling to targeted verification.
TransMem is proposed, a lightweight inference-time parametric memory module that transforms sparse historical hidden states from a frozen LLM backbone into reusable memory representations and introduces evidence-conditioned self-distillation to learn transferable memory utilization rather than task-specific knowledge.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.