1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.RO2024
Semantic Layering in Room Segmentation via LLMs
Taehyeon Kim, Byung-Cheol Min
In this paper, we introduce Semantic Layering in Room Segmentation via LLMs (SeLRoS), an advanced method for semantic room segmentation by integrating Large Language Models (LLMs)…
cs.LG2024
Revisiting Early-Learning Regularization When Federated Learning Meets Noisy Labels
Taehyeon Kim, Donggyu Kim, Se-Young Yun
In the evolving landscape of federated learning (FL), addressing label noise presents unique challenges due to the decentralized and diverse nature of data collection across client…
cs.LG2022★ 1 cited
Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search
Taehyeon Kim, Heesoo Myeong, Se-Young Yun
Knowledge Distillation (KD) has recently emerged as a popular method for compressing neural networks. In recent studies, generalized distillation methods that find parameters and a…