Semi-Instruct bridges the gap between Natural-Instruct and Self-Instruct to improve code Large Language Models by converting diverse but improper codes into proper instruction-code pairs.
The author proposes Semi-Instruct as a method to combine the strengths of Natural-Instruct and Self-Instruct for code large language models, addressing issues of diversity and correctness in instruction tuning data.