Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms — mentioned by bearobear

Wed, 12 Mar 2025 05:44:32 GMT

Last author here (I also did the DDIM paper, https://arxiv.org/abs/2010.02502). I know this is going to be very tricky math-wise (and in the paper we just wrote the most general thing to make reviewers happy), so I tried to explain the idea more easily under the blog post (https://lumalabs.ai/news/inductive-moment-matching). If you look at how a single step of the DDIM sampler interacts with the target timestep, it is actually just a linear function. This is obviously quite inflexible if we want to use it to represent a flexible function where we can choose any target timestep. So just add…

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Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms · HackerPapers discussions

Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms — mentioned by bearobear