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A Survey of Deep Learning Approaches for OCR and Document Understanding
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Documents are a core part of many businesses in many fields such as law, finance, and technology among others. Automatic understanding of documents such as invoices, contracts, and resumes is lucrative, opening up many new avenues of business. The fields of natural language processing and computer vision have seen tremendous progress through the development of deep learning such that these methods have started to become infused in contemporary document understanding systems. In this survey paper, we review different techniques for document understanding for documents written in English and consolidate methodologies present in literature to act as a jumping-off point for researchers exploring this area.
Forward citations
Cited by 7 Pith papers
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A document is worth a structured record: Principled inductive bias design for document recognition
Introduces a method to design structure-specific relational inductive biases for a base transformer architecture, enabling end-to-end transcription of documents with intrinsic structures, demonstrated on sheet music, ...
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The Documentation and Traceability Burden of the Indian EV Transition
The paper systematises India's EV compliance-document lifecycle into a two-layer evidence model, a six-stage lifecycle with four failure loci, an exergy-destruction analytic lens, and a six-problem research agenda.
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Q-Mask: Query-driven Causal Masks for Text Anchoring in OCR-Oriented Vision-Language Models
Q-Mask uses query-conditioned causal masks to separate text location from recognition in OCR VLMs, backed by a new benchmark and 26M-pair training dataset.
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CC-OCR V2: Benchmarking Large Multimodal Models for Literacy in Real-world Document Processing
CC-OCR V2 reveals that state-of-the-art large multimodal models substantially underperform on challenging real-world document processing tasks.
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Structured Data Extraction from Real Estate Documents using Clustering, Classification, and Large Language Models
A pipeline classifies 3965 real-estate questionnaires and extracts 35 structured attributes from 2781 selectable-text documents via DeepSeek R1, reporting Jaccard consistency 0.82.
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Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction
Survey proposing a taxonomy for document parsing into pipeline-based systems and VLM-driven unified models, reviewing components, metrics, benchmarks, and challenges.
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Cleansing Jewel: A Neural Spelling Correction Model Built On Google OCR-ed Tibetan Manuscripts
A Transformer augmented with a confidence score mechanism outperforms LSTM and GRU baselines on correcting OCR errors in paired Tibetan manuscript data.
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