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cs.LG2026
Mitigating Adaptive Attacks against Reasoning Models with Activation Consistency Training
Avidan Shah, Jannik Brinkmann, Rico Angell
As LLMs gain stronger reasoning capabilities, their extended chain-of-thought introduces new degrees of complexity for defending against adversarial jailbreaks and prompt injection…
cs.LG2026
On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation
Andy Han, Kristina Fujimoto, Avidan Shah +5
Aligned models can misbehave in several ways: they are often sycophantic, fall victim to jailbreaks, or fail to include appropriate safety warnings. Consistency training is a promi…
cs.LG2025
Jailbreak Transferability Emerges from Shared Representations
Rico Angell, Jannik Brinkmann, He He
Jailbreak transferability is the surprising phenomenon when an adversarial attack compromising one model also elicits harmful responses from other models. Despite widespread demons…