The Ingredients for Robotic Diffusion Transformers

发表时间：Oct 2024

论文链接：https://readpaper.com/pdf-annotate/note?pdfId=2536104770520270336&noteId=2609148347801754368

作者单位：Carnegie Mellon University

Motivation：In recent years roboticists have achieved remarkable progress in solving increasingly general tasks on dexterous robotic hardware by leveraging high capacity Transformer network architectures and generative diffusion models. Unfortunately, combining these two orthogonal（Transformer network architectures and generative diffusion models） improvements has proven surprisingly difficult, since there is no clear and well understood process for making important design choices.

解决方法：In this paper, we identify, study and improve key architectural design decisions for high-capacity diffusion transformer poli