64 citations · 358 across the 46 of their papers we have counts for
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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…
cs.CL2022★ 10 cited
Large Language Models Are Reasoning Teachers
Namgyu Ho, Laura Schmid, Se-Young Yun
Recent works have shown that chain-of-thought (CoT) prompting can elicit language models to solve complex reasoning tasks, step-by-step. However, prompt-based CoT methods are depen…
cs.CL2022
Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks
Jaehoon Oh, Jongwoo Ko, Se-Young Yun
Translation has played a crucial role in improving the performance on multilingual tasks: (1) to generate the target language data from the source language data for training and (2…