The current version of the Seed Diffusion model is optimized primarily for code generation and editing tasks, a domain chosen as a breakthrough for verifying the feasibility of discrete diffusion techniques. Code, as a highly structured form of language, best demonstrates the advantages of the diffusion model in terms of global understanding and parallel generation.
While technically applicable to natural language processing, the model is specifically designed for programming scenarios in terms of both training data and evaluation criteria. This focus enables Seed Diffusion to achieve performance breakthroughs in the code generation vertical, laying the groundwork for future technology extensions.
This answer comes from the articleSeed Diffusion: Validating High-Speed Language Models for Next-Generation ArchitecturesThe
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