ReasonBreak demonstrates up to 89% attack success on reasoning and 72% on trajectories in NVIDIA Alpamayo VLA models via black-box textual perturbations, introducing a reasoning-aware evaluation framework and benchmark for autonomous driving.
Excessive reasoning attack on reasoning llms.arXiv preprint arXiv:2506.14374, 2025
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GoAT-X introduces a Graph of Auditing Thoughts framework that combines static data flow extraction with structured LLM reasoning to identify semantic vulnerabilities in cross-chain token transactions.
Pruning removes 'unsafe tickets' from LLMs via gradient-free attribution, reducing harmful outputs and jailbreak vulnerability with minimal utility loss.
citing papers explorer
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ReasonBreak: Probing Vulnerabilities in Reasoning-Enabled Vision-Language-Action Models for Autonomous Driving
ReasonBreak demonstrates up to 89% attack success on reasoning and 72% on trajectories in NVIDIA Alpamayo VLA models via black-box textual perturbations, introducing a reasoning-aware evaluation framework and benchmark for autonomous driving.
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GoAT-X: A Graph of Auditing Thoughts for Securing Token Transactions in Cross-Chain Contracts
GoAT-X introduces a Graph of Auditing Thoughts framework that combines static data flow extraction with structured LLM reasoning to identify semantic vulnerabilities in cross-chain token transactions.
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Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMs
Pruning removes 'unsafe tickets' from LLMs via gradient-free attribution, reducing harmful outputs and jailbreak vulnerability with minimal utility loss.
- OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents