K$ Draft

"Drafting" in the context of large language models (LLMs) refers to the generation of preliminary text outputs, often used to accelerate inference or improve the quality of final text. Current research focuses on developing efficient drafting algorithms, such as self-speculative decoding and blockwise parallel decoding, to generate multiple drafts quickly and improve their coherence and accuracy. These advancements have significant implications for various applications, including faster LLM inference, improved clinical note generation, and enhanced software development workflows, ultimately increasing efficiency and productivity in diverse fields.