Flash-BoN Reranks Image Inference
gowthami_s · x · 2026-07-14
The author conducted experiments using image generation tasks, asking: given a prompt and 60 seconds, what is the best use of inference-time scaling.
They tested multiple inference-time scaling methods and found:
- Repeated intermediate verification is more time-consuming than expected
- Naive Best-of-N still consistently explores and is often stronger
- When changing the x-axis from NFE to actual seconds, the baseline rankings flip
This prompted them to rethink how to move beyond Best-of-N, leading to the proposal of Flash-BoN; the paper is on arXiv and will appear at ECCV 2026.
Related event: Flash-BoN: A Stronger Baseline for Diffusion Inference and Post-Training(7 posts)→
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