AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The performance of AI coding agents is highly dependent on their underlying coding rules. However, existing coding rules are typically hand-crafted and fixed, making the process labor-intensive and often suboptimal. In this work, we propose RuleEvolve, a self-evolving framework for coding rules. RuleEvolve maintains a...
The key findings show that while some detectors can identify attacks that rely on explicit textual instructions or visible image perturbations with moderate to high accuracy, they largely fail against attacks that omit explicit instructions or employ imperceptible perturbations.
This work proposes Visual Contrastive Self-Distillation, namely VCSD, which converts image-content removal into an on-policy self-distillation signal, and consistently outperforms matched OPSD across Qwen3-VL and Qwen3.5 models.
LongPIBench is introduced, a long-context benchmark for prompt injection covering 4 realistic application scenarios: paper peer review, resume screening, code review, and email summary, and the evaluation results reveal significant vulnerabilities of prompt injection defenses under long-context settings.
ContextLeak is developed, a malicious tool attack that induces the agent to both select the tool and disclose its context as input arguments, and significantly outperforms existing malicious tool attacks when adapted to this setting.
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