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cs.CV2025
Rethinking Generative Image Pretraining: How Far Are We From Scaling Up Next-Pixel Prediction?
Xinchen Yan, Chen Liang, Lijun Yu +3
This paper investigates the scaling properties of autoregressive next-pixel prediction, a simple, end-to-end yet under-explored framework for unified vision models. Starting with i…
cs.CV2021★ 1.2k cited
EfficientNetV2: Smaller Models and Faster Training
Mingxing Tan, Quoc V. Le
This paper introduces EfficientNetV2, a new family of convolutional networks that have faster training speed and better parameter efficiency than previous models. To develop this f…
cs.CV2017
Learning Transferable Architectures for Scalable Image Recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens +1
Developing neural network image classification models often requires significant architecture engineering. In this paper, we study a method to learn the model architectures directl…