Jaewon Chang — accepted AI-conference papers

2026

Rapid Poison: Practical Poisoning Attacks Against the Rapid Response Framework

David Huang, Jaewon Chang, Avidan Shah, Prateek Mittal, Chawin Sitawarin

ICML 2026spotlight

The Rapid Response (RR) framework (Peng et al., 2024), deployed in production systems including Anthropic’s ASL-3 safeguards (Anthropic, 2025), dynamically adapts jailbreak detection classifiers by generating synthetic training data from emerging attacks. We reveal that prompt injection can infiltra…

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2024

PubDef: Defending Against Transfer Attacks From Public Models

Chawin Sitawarin, Jaewon Chang, David Huang, Wesson Altoyan, David Wagner

ICLR 2024poster

Adversarial attacks have been a looming and unaddressed threat in the industry. However, through a decade-long history of the robustness evaluation literature, we have learned that mounting a strong or optimal attack is challenging. It requires both machine learning and domain expertise. In other wo…

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