Steerable Instruction Following Coding Data Synthesis with Actor-Parametric Schema Co-Evolution

arXiv:2604.16322v1 Announce Type: cross Abstract: Interpreting and following human instructions is a critical capability of large language models (LLMs) in automatic programming. However, synthesizing large-scale instruction-paired coding data remains largely unexplored and is particularly challenging when ensuring logical compatibility among multiple constraints. In this study, we propose IFCodeEvolve, an actor-schema co-evolution framework for instruction following coding data generation. By r