AI RESEARCH

MCTS-Judge: Test-Time Scaling in LLM-as-a-Judge for Code Correctness Evaluation

arXiv CS.AI

ArXi:2502.12468v2 Announce Type: replace-cross The LLM-as-a-Judge paradigm shows promise for evaluating generative content but lacks reliability in reasoning-intensive scenarios, such as programming. Inspired by recent advances in reasoning models and shifts in scaling laws, we pioneer bringing test-time computation into LLM-as-a-Judge, proposing MCTS-Judge, a resource-efficient, System-2 thinking framework for code correctness evaluation. MCTS-Judge leverages Monte Carlo Tree Search (MCTS) to decompose problems into simpler, multi-perspective evaluations.