Kim, Taesu

10 publications

NeurIPS 2025 GraLoRA: Granular Low-Rank Adaptation for Parameter-Efficient Fine-Tuning Yeonjoon Jung, Daehyun Ahn, Hyungjun Kim, Taesu Kim, Eunhyeok Park

NeurIPS 2024 Mixture of Scales: Memory-Efficient Token-Adaptive Binarization for Large Language Models Dongwon Jo, Taesu Kim, Yulhwa Kim, Jae-Joon Kim

AAAI 2024 OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models Changhun Lee, Jungyu Jin, Taesu Kim, Hyungjun Kim, Eunhyeok Park

ICML 2024 SLEB: Streamlining LLMs Through Redundancy Verification and Elimination of Transformer Blocks Jiwon Song, Kyungseok Oh, Taesu Kim, Hyungjun Kim, Yulhwa Kim, Jae-Joon Kim

NeurIPS 2023 Leveraging Early-Stage Robustness in Diffusion Models for Efficient and High-Quality Image Synthesis Yulhwa Kim, Dongwon Jo, Hyesung Jeon, Taesu Kim, Daehyun Ahn, Hyungjun Kim, Jae-Joon Kim

WACV 2023 Searching for Robust Binary Neural Networks via Bimodal Parameter Perturbation Daehyun Ahn, Hyungjun Kim, Taesu Kim, Eunhyeok Park, Jae-Joon Kim

ICMLW 2023 Squeezing Large-Scale Diffusion Models for Mobile Jiwoong Choi, Minkyu Kim, Daehyun Ahn, Taesu Kim, Yulhwa Kim, Dongwon Jo, Hyesung Jeon, Jae-Joon Kim, Hyungjun Kim

CVPRW 2022 GP22: A Car Styling Dataset for Automotive Designers Gyunpyo Lee, Taesu Kim, Hyeon-Jeong Suk

ICLR 2019 Double Viterbi: Weight Encoding for High Compression Ratio and Fast On-Chip Reconstruction for Deep Neural Network Daehyun Ahn, Dongsoo Lee, Taesu Kim, Jae-Joon Kim

ICLR 2018 Viterbi-Based Pruning for Sparse Matrix with Fixed and High Index Compression Ratio Dongsoo Lee, Daehyun Ahn, Taesu Kim, Pierce I. Chuang, Jae-Joon Kim