新闻
Learning When to Commit: Schedule Distillation for Fast Diffusion Language Models
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers propose dSpark, a schedule distillation framework that learns which tokens to generate first in diffusion language models to speed up parallel decoding.
- 为何重要
- Matters for engineers optimizing inference speed in diffusion-based language models, particularly for math reasoning and code generation workloads.
- 注意
- Results shown on specific model sizes and tasks; generalization to other domains and model scales remains unclear from this abstract.
- llm
- language model
- distill
- token
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