Papers by Kyeongpil Kang

2 papers
Restoring and Mining the Records of the Joseon Dynasty via Neural Language Modeling and Machine Translation (2021.naacl-main)

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Challenge: voluminous historical records are difficult to fully utilize since they are written in ancient languages and some parts are damaged over time.
Approach: They propose a multi-task learning approach to restore and translate historical documents using a self-attention mechanism.
Outcome: The proposed approach improves the accuracy of the translation task over baselines without multi-task learning.
Leveraging External Knowledge for Historical Document Restoration via Retrieval-Augmented Large Language Models (2026.findings-acl)

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Challenge: Historical documents suffer from illegibility due to physical deterioration and damage due to deteriorating materials.
Approach: a new framework leverages large language models with retrieval-augmented generation to restore historical documents. authors propose a framework that leverages implicit knowledge of pre-trained LLMs with explicitly retrieved external context.
Outcome: a new framework outperforms existing methods for restoration of historical documents in Korean . the proposed model can restore both general characters and named entities, the authors say .

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