Advanced Image Generation: Negative Prompt Optimization and Latent Classifier Guidance
Vaddi Charan Sai Nandan Reddy, Harini B, Chandana M S
cs.CV cs.LG
Abstract
We present a novel system that integrates negative prompt optimization via a fine-tuned sequence-to-sequence LLM and latent-space classifier guidance to improve the quality of images generated by Stable Diffusion. Our approach automatically generates optimized negative prompts, and employs a CNN-RNN hybrid classifier to evaluate and guide diffusion steps, rolling back low-quality latent updates. Experimental results demonstrate that our dual-guidance framework reduces artifacts and improves semantic fidelity compared to baseline diffusion.
Topics
Classified with taxonomy v2 on Wed, 2 Sept 2026.