arXiv Machine Learning August 4, 2026 By Raghavv Goel, Risheek Garrepalli, Sudhanshu Agrawal, Chris Lott, Mingu Lee, Fatih Porikli

A Comparative analysis of Layer-wise Representational Capacity in AR and Diffusion LLMs

Read the original on arXiv Machine Learning →

arXiv:2603. 07475v4 Announce Type: replace-cross Abstract: Autoregressive (AR) language models build representations incrementally via left-to-right prediction, while diffusion language models (dLLMs) are trained through full-sequence denoising.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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