Beyond pass@k: Redundancy-Aware RLVR for Multi-Sample Code Generation
Researchers have developed a new method called Redundancy-Aware RLVR to improve code generation from large language models. This approach addresses the issue of generated code samples being too similar to each other, which can hinder performance. By incorporating anti-redundancy rewards based on code similarity detection, the method aims to produce more diverse and executable code, often matching or surpassing existing techniques. AI