ACECODER: Enhancing Code Generation Models Through Automated Test Case Synthesis and Reinforcement Learning

MarkTechPost

Factuality

Ownership

ACECODER: Enhancing Code Generation Models Through Automated Test Case Synthesis and Reinforcement Learning

Code generation models have made remarkable progress through increased computational power and improved training data quality. State-of-the-art models like Code-Llama, Qwen2.5-Coder, and DeepSeek-Coder show exceptional capabilities across various programming tasks. These models undergo pre-training and supervised fine-tuning (SFT) using extensive coding data from web sources. However, the application of reinforcement learning (RL) in code genera…