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This work proposes PowerBench, a generation framework that derives interconnected heterogeneous operational data through a common dependency chain, and a synthetic dataset generated by this framework, comprising a generation framework that derives interconnected heterogeneous operational data through a common dependenc...
This work introduces PRISM Edit, which optimizes a single polysemous representation across temporal contexts and leverages the model's inherent modulation pathway to route it to temporally correct predictions without requiring any architectural modification.
EvoHarmBench is presented, the first dynamic adversarial evaluation framework for content moderation systems that employs an iterative optimization loop that evolves evasion strategies at the semantic-cluster level, while simultaneously optimizing for evasion success and human readability.
As large language models are increasingly deployed in real-world systems, safety failures can still lead to harmful outputs and dangerous misuse. We argue that the essence of safety is adversarial: many failures arise not from natural inputs alone, but from strategic attempts to evade model policies and safeguards. How...
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