Lightweight Pre-Trained Korean Language Model Based on Knowledge Distillation and Low-Rank Factorization

Lightweight Pre-Trained Korean Language Model Based on Knowledge Distillation and Low-Rank Factorization

Natural Language Processing (NLP) stands as a forefront of artificial intelligence research, empowering computational systems to comprehend and process human language as used in everyday contexts. Language models (LMs) underpin this field, striving to capture the intricacies of linguistic structure...

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Bibliographic Details
Main Authors: Jin-Hwan Kim, Young-Seok Choi
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Entropy
Subjects:
natural language processing
pre-trained language model
Korean language model
knowledge distillation
low-rank factorization
resource-constrained environment
Online Access:https://www.mdpi.com/1099-4300/27/4/379
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