字节跳动发布实验性扩散语言模型 Seed Diffusion Preview
字节跳动Seed团队宣布推出实验性扩散语言模型Seed Diffusion Preview，标志着在语言模型领域的一次重大技术突破。该模型旨在通过结构化的代码生成实验，验证离散扩散技术路线作为下一代语言模型基础框架的可行性。Seed Diffusion Preview在推理速度上取得了显著提升，达到每秒2146个tokens，相比同等规模的自回归模型提升了5.4倍，同时在多个代码生成基准测试中表现出与自回归模型相当的性能。
Seed Diffusion Preview的发布，旨在解决自回归（AR）模型在推理速度和全局控制方面的局限性。扩散模型通过从粗到精的生成范式，在图像和视频合成等连续数据领域取得了显著成功。然而，将扩散模型应用于自然语言等离散领域面临根本性挑战，主要在于标准扩散过程与离散状态空间的不兼
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