AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 5 of 265 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.
Recent advances in representation learning have highlighted the utility of constant-curvature models, such as hyperbolic and spherical spaces, for modeling complex data. Mixed-curvature models further enhance this by integrating multiple constant-curvature components. However, these models typically learn each componen...
In this work, we investigate the task of Federated Generalized Category Discovery (Fed-GCD), which aims to leverage labeled data from known classes to cluster unlabeled samples from both known and unknown classes through privacy-preserving collaboration among clients. Existing Fed-GCD methods predominantly emphasize im...
This work model high-order skeletal statistics via Gaussian embedding and propose a Riemannian network to capture inter-subject interactions and global correlations and shows that RGCN provides a competitive and geometrically grounded alternative for skeleton-based interaction recognition.
This work introduces POCI-Diff (Positioning Objects Consistently and Interactively), a framework that generates annotated synthetic scenes from explicit 3D bounding-box layouts with per-object semantic control and proposes a warping-free editing pipeline supporting object insertion, removal, and transformation via rege...
Modality-Agnostic Refusal Steering (MARS), a light-weight training-free approach that injects multimodal safety without the need for multimodal safety data, achieves consistent safety gains while preserving utility.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.