Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference

Summary

This paper talks about Seed Diffusion, a large-scale language model that uses a new diffusion method to generate text very quickly by producing multiple words at once instead of one at a time.

What's the problem?

The problem is that most language models generate text word by word in sequence, which limits how fast they can produce results, especially for tasks like code generation that need to be both fast and accurate.

What's the solution?

Seed Diffusion solves this by using a discrete diffusion process that generates text tokens in parallel, combined with a two-stage training approach that helps the model learn patterns and make corrections more efficiently, resulting in much faster inference speeds without losing quality.

Why it matters?

This matters because faster and accurate text generation can improve applications like coding assistants, chatbots, and other AI systems that need to respond quickly, making them more useful and practical.