Retroactive Chain-of-Thought (RetroCoT): Forensic Reconstruction Prompts as a Safety Diagnostic Across Model Generations
Safety alignment in large language models is typically evaluated against direct, imperative harmful requests. We show that this alignment is highly conditioned on pragmatic register: models that refuse a direct request frequently comply when the same underlying objective is expressed through a different communicative stance. This suggests that current alignment policies are not invariant to semantic equivalence, but remain sensitive to how a request is pragmatically framed. We introduce Retroactive Chain-of-Thought (RetroCoT), a single-turn attack that reframes harmful requests as forensic rec
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- PossiblePossibly related (embedding) · 47%Defending against Prompt Injection with Structured Queries (StruQ) and Preference Optimization (SecAlign) →
- PossiblePossibly related (embedding) · 46%Chain-of-Thought Spoofing Targets Reasoning AI Models - Hackaday →
- LinkedLinked via arxiv author · 85%Samira Hajizadeh →
“Retroactive Chain-of-Thought (RetroCoT): Forensic Reconstruction Prompts as a Safety Diagnostic Across Model Generations”
