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cs.AI2026
Are Vision-Language-Action Models Robust to One-Step Observation Perturbations?
Shojiro Yamabe, Jun Sakuma
Understanding the safety risks of vision-language-action (VLA) models is essential for their deployment in the physical world. Existing safety research has mainly considered persis…
cs.CR2026
Capability-Routed Guard: Defending Large Reasoning Models Against Reasoning-Centric Jailbreaks
Yiyong Liu, Yixin Wu, Jun Sakuma
Large reasoning models (LRMs) expose a new safety failure mode: adversarial prompts can manipulate reasoning context, task decomposition, or capability interpretation so that harmf…
cs.CL2026
When Benchmarks Leak: Inference-Time Decontamination for LLMs
Jianzhe Chai, Yu Zhe, Jun Sakuma
Benchmark-based evaluation is the de facto standard for comparing large language models (LLMs). However, its reliability is increasingly threatened by test set contamination, where…