Stay Within Your Bounds: Distance-Guided Decoding for Guaranteed Context-Free Grammar Compliance

Vincenzo Collura, Karim Tit, Eleonora Giunchiglia, Mike Papadakis, Maxime Cordy


Abstract
Grammar-constrained decoding helps large language models produce syntactically valid structured outputs, such as code, JSON, and SQL. For context-free grammars, many practical decoders enforce local prefix feasibility: each token must keep the current prefix extendable to some valid completion. Yet, under tokenizer–grammar mismatch and finite token budgets, feasible prefixes may still fail to reach acceptance. We propose a lookahead-guided decoding framework for context-free grammars based on pushdown automata. Offline, we compute bounded pushdown summaries with reachability labels and upper-bound distances to acceptance. Online, these estimates guide horizon-aware pruning and beam search. The resulting decoder is syntactically sound: every output is accepted by the target grammar. Experiments on JSON, SQL, and Linear Temporal Logic (LTL) show both consistent syntactic validity and improved completion quality over existing baselines.
Anthology ID:
2026.findings-emnlp.1752
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2026
Month:
October
Year:
2026
Address:
Budapest, Hungary
Editors:
Hung-Yi Lee, Sunipa Dev, Jessy Li, Desmond Elliott
Venue:
Findings
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
37479–37492
Language:
URL:
https://aclanthology.org/2026.findings-emnlp.1752/
DOI:
Bibkey:
Cite (ACL):
Vincenzo Collura, Karim Tit, Eleonora Giunchiglia, Mike Papadakis, and Maxime Cordy. 2026. Stay Within Your Bounds: Distance-Guided Decoding for Guaranteed Context-Free Grammar Compliance. In Findings of the Association for Computational Linguistics: EMNLP 2026, pages 37479–37492, Budapest, Hungary. Association for Computational Linguistics.
Cite (Informal):
Stay Within Your Bounds: Distance-Guided Decoding for Guaranteed Context-Free Grammar Compliance (Collura et al., Findings 2026)
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PDF:
https://aclanthology.org/2026.findings-emnlp.1752.pdf