Abstract: We introduce a neural generator that produces valid Lean 4 expressions directly at the kernel level, bypassing Lean's elaboration process. To train the generator, we implement Lean's core type checking in Python and integrate it into a reinforcement learning environment that assigns rewards for well-typed subexpressions. We evaluate the model's ability to learn and adapt within this environment.
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