AI in Production

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Data Extraction from Invoice Type Documents using Large Language Models
Towards tailored made AI models that adapt to changes and match the needs and demands of a dynamic real-world environment.
 • 
Mihaela Kakarigi
 and 
Zeljko
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Multi-Task Learning with Intermediate Continual Learning for Industry NLP Use Cases
Utilizing adapters and hypernetworks to efficiently, effectively, and continuously train multiple tasks
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Tin Ferković
Exploring State-of-the-Art Models for Document-Level Entity Relation Extraction
Document-level entity relation extraction involves identifying and categorizing relationships between entities mentioned within whole documents, rather…
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Dunja Smigovec
Named Entity Recognition Using Question Answering in Zero- and Few-Shot Settings
The human race produces copious amounts of documents daily to aid its effective functioning. Even though digitalization allows the automatic processing…
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Luka Pavlović
Secure Your Kubernetes Web Application Using Gatekeeper And Keycloak
In certain scenarios, you may need to integrate an authentication layer into a basic application or tool that doesn't demand complex authentication…
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Bojan
Annotation Team Lead and Teamwork
Document annotation is a crucial step in training AI models, particularly in the context of Natural Language Processing (NLP). It involves adding labels…
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Dragan Kraljević
Named Entity Recognition Using a Pre-Trained LayoutLMv2 Model
The amount of data generated by humans is ever-increasing, much of which is stored in documents and forms that need to be analyzed to extract relevant…
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Marko Cvjetko
Named Entity Recognition using BERT on Subsampled Datasets
The Named-Entity Recognition (NER) system I worked on during my internship at doXray is part of a live production system. At doXray, models in…
 • 
Eva Jagodić
 and 
Bruno Šarlija
AI in Production
AI in Production
From customers and annotations to large language models and AI platforms, everything doXray does to run AI in production.
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