[QA] Training Language Models on Synthetic Edit Sequences Improves Code Synthesis

The paper presents LintSeq, a synthetic data generation algorithm that refactors code into edit sequences, improving LLM performance in code synthesis and achieving state-of-the-art results with smaller models. https://arxiv.org/abs//2410.02749 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers