2025
ACL
ACL 2025
Arctic-TILT. Business Document Understanding at Sub-Billion Scale
Abstract
AbstractThe vast portion of workloads employing LLMs involves answering questions grounded on PDF or scanned content. We introduce the Arctic-TILT achieving accuracy on par with models 1000× its size on these use cases. It can be finetuned and deployed on a single 24GB GPU, lowering operational costs while processing 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, essential for processing files in large-scale or time-sensitive enterprise environments. We release Arctic-TILT weights and an efficient vLLM-based implementation on a permissive license.
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Interdisciplinary Bridge
— Computer Vision and Deep Learning and Machine Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Natural Language Processing > Applications > Question Answering
Natural Language Processing > Resources & Methods > Large Language Models
Deep Learning > Models > Large Language Models
Computer Vision > Domain-Specific > Document Analysis
Machine Learning > Learning Types > Retrieval-Augmented Generation
Deep Learning > Optimization & Theory > Efficient Computing
Natural Language Processing > Applications > Document Analysis