Papers by Seokhwan Jang

1 papers
Language, OCR, Form Independent (LOFI) pipeline for Industrial Document Information Extraction (2024.emnlp-industry)

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Challenge: Existing models for low-resource language (LRL) documents are limited in semantic entity extraction, and there are limitations in SER from word level results.
Approach: They propose a pipeline for Document Information Extraction (DIE) in low-resource language (LRL) business documents that solves language, Optical Character Recognition (OCR), and form dependencies through flexible model architecture, a token-level box split algorithm, and the SPADE decoder.
Outcome: Experiments on Korean and Japanese documents show that the pipeline performs well in the Semantic Entity Recognition task without pre-training.

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