Multimodal Document Understanding for Invoice Processing: A Case Study of Error Cost Distribution

Authors

  • Teresinha Rebimbas Centre for Computer Vision, Pinhal Centre for Machine Intelligence, Leiria, Portugal Author
  • Zsombor Hetenyi Centre for Language Technology, Cserhat Centre for Machine Intelligence, Salgotarjan, Hungary Author
  • Bjarke Sonnichsen Department of Machine Learning Engineering, Stevns Centre for Machine Intelligence, Store Heddinge, Denmark Author

DOI:

https://doi.org/10.5281/zenodo.22660968

Keywords:

Multimodal Document Understanding for Invoice Processing; Applied machine learning; Evidence synthesis; Production deployment; MLOps

Abstract

Multimodal Document Understanding for Invoice Processing 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 multimodal
document understanding for invoice processing, 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. "Multimodal Document Understanding for Invoice Processing: a empirical analysis". Knowl Based Syst 32(2014): 432-443. DOI: 10.17219/acem/208596

Dumitrescu A, Andric D, et al. "Multimodal Document Understanding for Invoice Processing: a ablation study". IEEE Trans Neural Netw Learn Syst 34(2017): 443-455. DOI: 10.7759/cureus.104086

Eriksdottir B, Brankovic E, et al. "Multimodal Document Understanding for Invoice Processing: a reproducibility study". Proc KDD 36(2020): 454-467. DOI: 10.1038/s41746-023-00852-5

Farkas I, Ionescu F, et al. "Multimodal Document Understanding for Invoice Processing: a large-scale evaluation". Proc AAAI 38(2023): 465-479. DOI: 10.1016/j.mayocpiqo.2022.09.004

Grabowski P, Petrescu G, et al. "Multimodal Document Understanding for Invoice Processing: a case study". IEEE Trans Knowl Data Eng 40(2014): 476-482. DOI: 10.1177/08404704241291226

Hendriksen W, Wojcik H, et al. "Multimodal Document Understanding for Invoice Processing: a survey". J Artif Intell Res 42(2017): 487-494. DOI: 10.1093/medlaw/fwad013

Ionescu F, Foscarini I, et al. "Multimodal Document Understanding for Invoice Processing: a comparative analysis". ACM Comput Surv 44(2020): 498-506. DOI: 10.2196/89834

Jankowiak G, Grabowski J, et al. "Multimodal Document Understanding for Invoice Processing: a field deployment report". Neural Comput Appl 46(2023): 509-518. DOI: 10.1007/s10916-024-02104-9

Kowalczyk N, Novotna K, et al. "Multimodal Document Understanding for Invoice Processing: a benchmark study". Expert Syst Appl 8(2014): 520-530. DOI: 10.3389/fdgth.2026.1896184

Lindqvist U, Urbanek L, et al. "Multimodal Document Understanding for Invoice Processing: a systematic evaluation". Inf Sci 10(2017): 531-542. DOI: 10.3390/diagnostics15162117

Marchetti D, Doncheva M, et al. "Multimodal Document Understanding for Invoice Processing: a empirical analysis". Pattern Recognit 12(2020): 542-554. DOI: 10.4103/jrpp.jrpp_20_65

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Published

2026-02-02

Issue

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

Section

Articles

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