AR→Diffusion 2x Speedup

·2026.04.14 21:23

Key point

A method that converts auto-regressive models into diffusion models to make them **more than 2x** faster.

Details

Presents a new method for converting auto-regressive models into diffusion models.

The key advantages are as follows.

Aims for more than 2x speedup.
Proposes full compatibility with existing inference stacks.
A direction that boosts inference efficiency without rewriting a new model from scratch.

In summary, the claim is that by moving existing auto-regressive generation methods to the diffusion family, you can run them faster while still fully leveraging current inference infrastructure.

machine-learning inference autoregressive-models diffusion-models speedup model-conversion

Read originalShare on Threads

This summary was generated automatically by AI. Check the original for the author's claims and context. Copyright belongs to the original author.

Our guide explains how the AI works. Report summary errors, attribution issues, or removal requests via Contact.