When Guidance Becomes a Guard: Early Interception of Unsafe Inputs in Text-to-Image Generation

Summary

Researchers asked whether text-to-image diffusion models can flag unsafe or adversarial prompts before an image is generated, rather than filtering outputs afterward. They propose Conditional Semantic Trajectory Interception (CSTI), which compares conditional and unconditional responses at early checkpoints, trained on canonical concept and safe examples without attack samples. Across five generators, four adversarial attack collections and two NSFW datasets, CSTI achieves the strongest overall performance among six baselines at a matched 5% FPR, and cuts generation latency by over 60% on intercepted paths.