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This GitHub repo hosts a reading list and resource hub about synthetic data for large language models (LLMs), focusing on data generated by LLMs for LLMs. It aggregates papers, tools, and blogs across surveys, methods, datasets, and applications such as reasoning, code generation, alignment, and beyond. The goal is to help researchers and practitioners explore, generate, evaluate, and apply synthetic data to improve LLM performance and reliability.
AI named Awesome LLM Synthetic Data from December 2025 to February 2026.