Sayak Paul

We show that best-of-N (BoN) is a much better baseline for diffusion test-time scaling when done right. Our core premise is that NFEs provide a false sense of efficiency by ignoring several underlying factors, such as verifier costs. We then introduce Flash-BoN, which encourages broader exploration of samples than repeated intermediate validation. Overall, our findings are simple: 1. Report NFEs AND wallclock time (so that the algorithms that verify more frequently are validated appropriately) 2. Spend (test-time) compute on exploring more rather than frequent intermediate validations When we combined the two, we see that BoN either outperforms or is on par with other fancier techniques. Extended thread 👇