Structured Output Constraints in Language Model Applications: A Review of Grammar and Schema Enforcement

Authors

  • Stijn Steenackers Centre for Language Technology, Herve Centre for Machine Intelligence, Verviers, Belgium Author
  • Egill Hallgrimsson Department of Software Engineering, Snaefellsnes Institute of Applied Artificial Intelligence, Stykkisholmur, Iceland Author
  • Aveline Winterbourne Department of Machine Learning Engineering, Orkney Institute of Data Science, Kirkwall, United Kingdom Author

DOI:

https://doi.org/10.5281/zenodo.22660994

Keywords:

Structured Output Constraints in Language Model Applications; Applied machine learning; Evidence synthesis; Production deployment; MLOps

Abstract

Structured Output Constraints in Language Model Applications is an area of active development in applied machine learning,
with evidence that has accumulated unevenly across its component questions. We review the current evidence base for structured
output constraints in language model applications, spanning methodological, implementation, governance, and cost dimensions,
focusing on where practice has converged and where it continues to vary, and set out the practical considerations relevant to a
team considering its adoption. We conclude that selective, context-specific use is best supported by the evidence currently
available, rather than uniform adoption or avoidance

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Castellani R, Ristic C, et al. "Structured Output Constraints in Language Model Applications: a empirical analysis". Knowl Based Syst 32(2014): 432-443. DOI: 10.1038/s41746-023-00852-5

Dumitrescu A, Andric D, et al. "Structured Output Constraints in Language Model Applications: a ablation study". IEEE Trans Neural Netw Learn Syst 34(2017): 443-455. DOI: 10.1016/j.mayocpiqo.2022.09.004

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Farkas I, Ionescu F, et al. "Structured Output Constraints in Language Model Applications: a large-scale evaluation". Proc AAAI 38(2023): 465-479. DOI: 10.1093/medlaw/fwad013

Grabowski P, Petrescu G, et al. "Structured Output Constraints in Language Model Applications: a case study". IEEE Trans Knowl Data Eng 40(2014): 476-482. DOI: 10.2196/89834

Hendriksen W, Wojcik H, et al. "Structured Output Constraints in Language Model Applications: a survey". J Artif Intell Res 42(2017): 487-494. DOI: 10.1007/s10916-024-02104-9

Ionescu F, Foscarini I, et al. "Structured Output Constraints in Language Model Applications: a comparative analysis". ACM Comput Surv 44(2020): 498-506. DOI: 10.3389/fdgth.2026.1896184

Jankowiak G, Grabowski J, et al. "Structured Output Constraints in Language Model Applications: a field deployment report". Neural Comput Appl 46(2023): 509-518. DOI: 10.3390/diagnostics15162117

Kowalczyk N, Novotna K, et al. "Structured Output Constraints in Language Model Applications: a benchmark study". Expert Syst Appl 8(2014): 520-530. DOI: 10.4103/jrpp.jrpp_20_65

Lindqvist U, Urbanek L, et al. "Structured Output Constraints in Language Model Applications: a systematic evaluation". Inf Sci 10(2017): 531-542. DOI: 10.3389/fdgth.2026.1763884

Marchetti D, Doncheva M, et al. "Structured Output Constraints in Language Model Applications: a empirical analysis". Pattern Recognit 12(2020): 542-554. DOI: 10.2196/48297

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Ostrowski L, Lindqvist O, et al. "Structured Output Constraints in Language Model Applications: a reproducibility study". ACM Trans Softw Eng Methodol 16(2014): 564-578. DOI: 10.3389/fdgth.2026.1699005

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Published

2026-04-14

Issue

Vol. 5 No. 1 (2026): vol 5 issue 1 2026

Section

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