Improving Visual Representation Alignment Generation with GRPO
Recent diffusion transformers have demonstrated strong image synthesis capabilities but remain inefficient to train due to weak alignment between generative and discriminative representations. While representation alignment frameworks such as REPA improve convergence by aligning noisy denoising features with pretrained visual encoders, their externally supervised alignment loss is static and lacks adaptivity during training and inference. Existing methods rely on fixed cosine alignment or contra
Record details
Published: 30 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Safety & alignment
Retrieved: 14 July 2026
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ethics.ai (30 May 2026), “Improving Visual Representation Alignment Generation with GRPO,” evidence record 3402, https://ethics.ai/record/3402 (originally published by arXiv).
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