sat-solvers

SAT-RL is a reinforcement learning framework that trains LLMs to interact with symbolic solvers like Z3 through multi-turn tool execution, combining synthetic data generation, supervised warm-up on solver-augmented traces, and solver-grounded RL with tool-aware rewards to improve logical reasoning on in-domain and out-of-domain tasks.