AI RESEARCH
Verifier Threshold: An Efficient Test-Time Scaling Approach for Image Generation
arXiv CS.CV
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ArXi:2512.08985v3 Announce Type: replace Image generation has emerged as a mainstream application of large generative models. Just as test-time compute and reasoning have improved language model capabilities, similar benefits have been observed for image generation models. In particular, searching over noise samples for diffusion and flow models has been shown to scale well with test-time compute.