2026
Breaking the Lock-in: Diversifying Text-to-Image Generation via Representation Modulation
ICML 2026poster
Recent text-to-image models built on large-scale Transformer backbones and flow-based objectives deliver strong text–image alignment and high visual quality, yet often produce overly similar samples under a fixed prompt. Existing diversity-enhancement methods can increase sample-to-sample variation,…