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cs.AI2026
Stress Testing Concept Erasure with Large Language Model Agents
Yuyang Xue, Feng Chen, Zhihua Liu +4
Concept erasure aims to remove semantic concepts from a trained generative model and is increasingly important for responsible AI deployment. However, verifying whether a model has…
cs.AI2026
CSEval: A Framework for Evaluating Clinical Semantics in Text-to-Image Generation
Robert Cronshaw, Konstantinos Vilouras, Junyu Yan +4
Text-to-image generation has been increasingly applied in medical domains for various purposes such as data augmentation and education. Evaluating the quality and clinical reliabil…