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dRAE: Representation Autoencoder with Hyper-Spherical Codes

9 upvotes · 24 JUL 2026 · Tianren Ma, Lin Long, Chuyan Chen et al.

This paper develops a new method for quantizing high-dimensional visual representations into discrete codes that can be used with language models, allowing for more efficient and scalable training. Practitioners might care because it could enable the use of large language models on devices with limited memory.

representation learningquantizationautoencodershyper-spherical codesangular routing