AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 5 of 134 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.
Given an oriented graph $\vec{G}$ and a subset of vertices $X \subseteq V(\vec{G})$, the \emph{inversion} of $X$ is the operation that reverses the orientation of every arc with both endpoints in $X$. For a simple graph $G$, the inversion diameter $\operatorname{diam}(I(G))$ is the maximum distance between two orientat...
This work proposes embodiment-conditioned safety filtering, in which a Hamilton-Jacobi reachability-based value function and its corresponding safety-maximizing policy are shared across robots, and performs Hamilton-Jacobi reachability analysis directly in latent space so that the learned safety concepts can generalize...
Multimodal Large Language Models (MLLMs) have demonstrated great performance, yet they often suffer from severe modality misalignment when confronted with densely constrained spaces for interior design. Due to the loss of high-frequency local topological details and fine-grained aesthetic shifts during visual encoding,...
MOEA/D-TCM is proposed, a decomposition-based multi-objective evolutionary framework tailored to node-set optimization in multi-layer networks that represents each solution as an observer set and combines a set-structure-adaptive evolutionary strategy with stable-state replacement and neighborhood adjustment to coordin...
This paper investigates language-conditioned safety filtering, in which a Hamilton-Jacobi safety actor and critic are conditioned on language-specified constraints, and provides evidence that language-conditioned safety filters reduce constraint violations and exhibit partial transfer to unseen constraint instances.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.