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This work argues RSI must next operate across real, diverse scientific, engineering, and meta-scientific domains, not where formal evaluation is merely tractable, and presents MetaRSI-v1, where improvement is the scheduled composition of three typed operators over one unified paradigm.
It is suggested that LLMs differ not only in baseline risk disposition, but also in the risk signals they respond to and the flexibility with which they adjust, providing a behavioural basis for auditing risk-sensitive decision-making in interactive settings.
This work shows that scenario-wrapped prompts activate internal scenario directions whose causal steering consistently reduces refusal scores, and proposes Concept2Scenario, a concept-based attribution framework for vulnerable scenario discovery that instantiates a broad concept space with a sparse autoencoder, transla...
ReFrame is a training-free multimodal input reframing framework where two agents share a lightweight locally deployed MLLM: the evidence-generation agent constructs complementary risk and utility evidence, and the rewrite-and-routing agent converts it into a safe proxy prompt and image-routing decision before calling t...
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