Stitched Value Model for Diffusion Alignment
For practical use, diffusion- or flow-based generative models must be aligned with task-specific rewards, such as prompt fidelity or aesthetic preference. That alignment is challenging because the reward is defined for clean output images, but the alignment procedure requires value function estimates at noisy intermediate latents. Existing methods resort to Tweedie-style or Monte Carlo approximations, trading off estimator bias against computational cost: Tweedie estimates are efficient but bias
Record details
Published: 19 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Safety & alignment
Retrieved: 14 July 2026
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ethics.ai (19 May 2026), “Stitched Value Model for Diffusion Alignment,” evidence record 4023, https://ethics.ai/record/4023 (originally published by arXiv).
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