Forgotten Horizons in Concept Erasure: Safeguarding Close-Proximity Concepts in Text-to-Image Models

Text-to-image models (AI systems that generate images from written descriptions) sometimes memorize harmful concepts that need to be removed, but existing removal techniques accidentally damage the model's ability to generate similar concepts. Researchers propose SCPC, a framework that erases target concepts while protecting semantically similar ones, using a technique called semantic-agnostic knowledge distillation (matching the erased model's output to the original model's output without relying on concept meaning).