Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms 事件

Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms arXiv:2503.07154v3 Announce Type: replace-cross Abstract: Generative pre-training is often framed through a false dichotomy between autoregressive models for discrete signals and diffusion models for continuous signals. We argue that the dichotomy is false because it conflates model family, data representation, training objective, and inference procedure. Autoregression is an inference procedure that expands a sequen