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Arctic-TILT. Business Document Understanding at Sub-Billion Scale

Michał Pietruszka
Paweł Józiak
Łukasz Garncarek
Paweł Liskowski
Julita Ołtusek
Artur Zawłocki
Łukasz Duhr
Paweł Dyda
Michał Turski
Main:7 Pages
12 Figures
Bibliography:4 Pages
5 Tables
Appendix:5 Pages
Abstract

The vast portion of workloads employing LLMs involves answering questions grounded on PDF or scan content. We introduce the Arctic-TILT achieving accuracy on par with models 1000×\times its size on these use cases. It can be fine-tuned and deployed on a single 24GB GPU, lowering operational costs while processing Visually Rich Documents with up to 400k tokens. The model establishes state-of-the-art results on seven diverse Document Understanding benchmarks, as well as provides reliable confidence scores and quick inference, which are essential for processing files in large-scale or time-sensitive enterprise environments.

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