this post was submitted on 21 May 2025
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Traditional autoregressive language models generate text sequentially, one token at a time, leading to slower outputs with limited coherence and quality.

Diffusion models are an alternative approach. Instead of direct prediction, they iteratively refine noise, enabling faster generation, dynamic error correction, and greater control. This makes them particularly effective for editing tasks, including in math and code.

https://github.com/ML-GSAI/LLaDA

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[–] burlemarx@lemmygrad.ml 2 points 16 hours ago

Nice, another improvement on existing LLM models. It's impressive how fast the Chinese are advancing in this technology. The nice thing is that they made their work open source as well.