Evaluation without Generation: Non-Generative Assessment of Harmful Model Specialization with Applications to CSAM
Auditing the fine-tunes of open-weight generative models for harmful specialization has become a new governance challenge for model hosting platforms. The standard toolkit, generative evaluation via curated prompts or red-teaming, does not scale to platform-level auditing and breaks down entirely for domains like CSAM where generation is legally constrained. This motivates the Evaluation without Generation problem: assessing model capabilities without producing outputs. We argue that in such set
Record details
Published: 28 April 2026
Source: arXiv
Category: Research
Topics: Regulation · Safety & alignment · Transparency
Retrieved: 14 July 2026
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ethics.ai (28 April 2026), “Evaluation without Generation: Non-Generative Assessment of Harmful Model Specialization with Applications to CSAM,” evidence record 5283, https://ethics.ai/record/5283 (originally published by arXiv).
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