AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Capacity-Aware Selective Hashing (CASH) is proposed, which significantly improves Hamming-space utilization through bit-level selective allocation under a fixed capacity budget, enabling stable continual learning while preserving long-term code compatibility.
Multi-modal hashing converts high-dimensional features into compact binary codes while preserving semantic similarity, thereby achieving high performance with lower storage and computational costs. However, existing methods generally overly depend on discrete supervisory information, ignoring the ambiguity of labels an...
MMJailBench is introduced, a factorized benchmark that systematically varies and combines these factors under controlled configurations, enabling fine-grained comparison and factor-level attribution and a modular multimodal jailbreak evaluation suite with full and lightweight configurations, multiple judge options, and...
ActFovea is introduced, a plug-and-play safeguarding framework that detects and mitigates runtime failures of vision-language-action policies without retraining or modifying the underlying VLA policy.
UniTexture is introduced, a cross-task universal adversarial texture attack that uses a single textured 3D object to induce targeted deviations in VLA action predictions across multiple tasks and reveals shared cross-task vulnerabilities in multitask VLAs that can be systematically exploited through a single adversaria...
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