IAFS is a training-free iterative inference-time scaling framework that uses adaptive frequency-aware particle fusion to resolve the perception-fidelity conflict in diffusion super-resolution models, outperforming prior scaling strategies.
Ctrl-z sampling: Diffusion sampling with controlled random zigzag explorations.arXiv preprint arXiv:2506.20294, 2025
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ABSS ranks diffusion seeds by early cross-attention strength to prompt core tokens and retains only the top-k for full generation, yielding consistent gains in alignment and quality on Stable Diffusion variants.
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Iterative Inference-time Scaling with Adaptive Frequency Steering for Image Super-Resolution
IAFS is a training-free iterative inference-time scaling framework that uses adaptive frequency-aware particle fusion to resolve the perception-fidelity conflict in diffusion super-resolution models, outperforming prior scaling strategies.
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Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection
ABSS ranks diffusion seeds by early cross-attention strength to prompt core tokens and retains only the top-k for full generation, yielding consistent gains in alignment and quality on Stable Diffusion variants.