Dec 09 2024 4 mins 3
In this episode, we discuss o1-Coder: an o1 Replication for Coding by Yuxiang Zhang, Shangxi Wu, Yuqi Yang, Jiangming Shu, Jinlin Xiao, Chao Kong, Jitao Sang. The paper discusses "O1-CODER," which aims to replicate OpenAI's o1 model focusing on coding tasks, utilizing reinforcement learning and Monte Carlo Tree Search to boost System-2 thinking. The framework involves a Test Case Generator for code testing, MCTS for code data generation, and iterative model refinement to transition from pseudocode to full code generation. It highlights challenges in deploying o1-like models, suggests a shift towards System-2 paradigms, and plans to update resources and findings on their GitHub repository.
