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arXiv AI By Gabriele Tuccio, Antonino Furnari, Aldo Gangemi, Misael Mongiov\`{\i}

GrammarRL: Effective Grammar-Constrained Decoding via Reinforcement Learning

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GrammarRL introduces a label‑free reinforcement learning approach that adapts language models to grammar constraints without annotated data. It optimizes two self‑supervised rewards—direct and reverse—using a Reinforce Leave‑One‑Out objective over grammar‑constrained rollouts, and regularizes toward a frozen base model. Experiments on sign‑language gloss translation, hierarchical text classification, and named entity recognition with Llama models show consistent gains over constrained greedy decoding and competitive performance to beam search while keeping inference cost low.

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