AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Glitch tokens are anomalous vocabulary entries that can cause large language models (LLMs) to produce outputs inconsistent with their inputs. Existing repair methods require access to model internals, making them impractical for frozen checkpoints. We investigate whether glitch tokens can be repaired outside the model...
SciGuard is proposed, an agent-based guardrail that employs large language models, tools and external knowledge to assess and control risks in scientific AI interactions, and achieves a state-of-the-art harmlessness score on red-teaming queries, while maintaining high performance on benign tasks, without sacrificing sc...
Dual-stage Native Attribution (DNA) is proposed, a coarse-to-fine framework that follows this hierarchy without additional neural-network training that achieves 89.11% end-to-end attribution accuracy on a task where random guessing accuracy is below 1% and outperforms the strongest baseline by 33.81% even when AEDR is...
FARI is proposed, a one-step inversion framework paired with lightweight adversarial LoRA fine-tuning of the denoiser for watermark extraction that surpasses 50-step DDIM inversion on watermark-verification robustness while dramatically reducing inference time.
This work determines what each reported result implies for that question: how much help with harmful tasks the service still gives an attacker who keeps adapting or finds another way in.
This work studies the channel delivering search and page observations is a fragile security boundary and introduces Authority-Chain Hijack (ACH), an expert-refined strategy that turns isolated search-result and page-content manipulations into a coherent evidence chain across seemingly corroborating sources.
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