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Scaling Transformer Energy-based Models For High Quality Image Synthesis
Jungsoo Lee, Alexi Gladstone, Yilun Du
Energy-Based Models (EBMs) are a flexible class of generative models that decouple probabilistic modeling from the generation process. This decoupling directly enables compositiona…
Explorative Modeling: Unlocking a Third Pretraining Axis and End-to-End Generation
Alexi Gladstone, Heng Ji, Yilun Du
The deep learning revolution, kicked off by AlexNet, taught us that end-to-end training beats decomposing a problem into hand-designed stages. Generative modeling, however, has rem…
You Don't Need Strong Assumptions: Visual Representation Learning via Temporal Differences
Ninad Daithankar, Alexi Gladstone, Yann LeCun +1
Progress in AI has largely been driven by methods that assume less. As compute and data increase, approaches with weaker inductive biases generally outperform those with stronger a…
Assessing the Creativity of Large Language Models: Testing, Limits, and New Frontiers
Samuel Schapiro, Alexi Gladstone, Jonah Black +1
Measuring the creativity of large language models (LLMs) is essential for designing methods that can improve creativity and for enhancing our scientific understanding of this abili…