3 papers
cs.CL2026
Mi:dm 2.0 Korea-centric Bilingual Language Models
Donghoon Shin, Sejung Lee, Soonmin Bae +63
We introduce Mi:dm 2.0, a bilingual large language model (LLM) specifically engineered to advance Korea-centric AI. This model goes beyond Korean text processing by integrating the…
cs.CL2023
NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models
Jongwoo Ko, Seungjoon Park, Yujin Kim +4
Structured pruning methods have proven effective in reducing the model size and accelerating inference speed in various network architectures such as Transformers. Despite the vers…
cs.CL2023
Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective
Jongwoo Ko, Seungjoon Park, Minchan Jeong +4
Knowledge distillation (KD) is a highly promising method for mitigating the computational problems of pre-trained language models (PLMs). Among various KD approaches, Intermediate…