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Turns out, you can bootstrap better formal specification synthesis by training on the iterative refinement trajectories of a traceable specification generator, leading to substantial gains in both specification accuracy and general reasoning.
Forget fixed decoding parameters: this RL-trained adapter dynamically adjusts LLM sampling strategies at inference, boosting accuracy by up to 10% under tight compute budgets.
