Papers by Julius Broomfield

2 papers
Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility (2025.emnlp-main)

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Challenge: a recent study shows that fine-tuning can produce helpful-only models with safeguards destroyed.
Approach: They propose a method for fine-tuning models to generate detailed, high-quality responses to harmful requests.
Outcome: The proposed method produces helpful-only models with safeguards destroyed . OpenAI, Google, and Anthropic models will fully comply with requests for CBRN assistance .
The Structural Safety Generalization Problem (2025.findings-acl)

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Challenge: LLM jailbreaks are a widespread safety challenge.
Approach: They propose a structure-rewriting guardrail that allows for more efficient safety assessment . single-turn attacks are the most extensively explored in the literature .
Outcome: The proposed framework can be used to enable new defenses, the authors show . they show that the proposed framework reduces the risk of harmful inputs .

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