AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 7 of 16 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.
This work proposes ReGap, a data-free attack that recovers private associations using task structure, filters them by answer-token likelihood, and updates the target model via low-rank adaptation, which requires neither target answers nor auxiliary genuine private supervision.
SAVER is introduced, a transition-centered framework in which Substrate locates reusable influence, Adaptation captures how it changes, Violation identifies compromised safety attributes, Exposure marks where failures become observable, and Response assesses containment, repair, or revocation.
Deep Reinforcement Learning (DRL) has demonstrated remarkable capabilities in domains such as robotics, finance, and autonomous systems. With the increasing cost of training, DRL models are increasingly shared and reused via model marketplaces, cloud platforms, and open-source repositories. This trend exposes DRL syste...
This work introduces PROSE (Provenance through Relational Organization of Semantic Expression), replacing fixed query sets with a target semantical domain and brittle response keys with semantic structures internalized as domain-conditioned response behavior.
IntraGuard is proposed, a black-box, venue-agnostic defense framework grounded in the structural--visual decoupling inherent to the PDF that achieves a defense success rate of up to 84%, while preserving peer-review invariance for human reviewers.
SkillShift is presented, a constrained black-box framework for covert policy steering without explicit target command injection or task hijacking that combines semantically plausible policy edits with hierarchical validation, failure-guided optimization, and strategy compression to preserve effectiveness, output validi...
This study unveils the capability of attackers to generate adversarial policies even when restricted to partial observations of the victims in multi-agent competitive environments, and proposes a novel black-box attack (SUB-PLAY) that incorporates the concept of constructing multiple subgames to mitigate the impact of...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.