UniEvo-VL: Self-Distillation Training for Multimodal Model Self-Improvement

UniEvo-VL is a self-evolving framework that enables multimodal models to improve through self-distillation, using their own critiques as privileged information to train a single model as both teacher and student. Experiments on Qwen-image-2512 showed performance gains on GenEval and GenEval2 Soft-TIFA, though improvements were not uniform across all tasks.