Lee, Jae W.

10 publications

NeurIPS 2025 DP-LLM: Runtime Model Adaptation with Dynamic Layer-Wise Precision Assignment Sangwoo Kwon, Seong Hoon Seo, Jae W. Lee, Yeonhong Park

ICCV 2025 FastPoint: Accelerating 3D Point Cloud Model Inference via Sample Point Distance Prediction Donghyun Lee, Dawoon Jeong, Jae W. Lee, Hongil Yoon

ICML 2025 FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials Seung Yul Lee, Hojoon Kim, Yutack Park, Dawoon Jeong, Seungwu Han, Yeonhong Park, Jae W. Lee

ICML 2025 GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance Jinuk Kim, Marwa El Halabi, Wonpyo Park, Clemens Js Schaefer, Deokjae Lee, Yeonhong Park, Jae W. Lee, Hyun Oh Song

NeurIPS 2025 KVzip: Query-Agnostic KV Cache Compression with Context Reconstruction Jang-Hyun Kim, Jinuk Kim, Sangwoo Kwon, Jae W. Lee, Sangdoo Yun, Hyun Oh Song

NeurIPS 2025 NestedFP: High-Performance, Memory-Efficient Dual-Precision Floating Point Support for LLMs Haeun Lee, Omin Kwon, Yeonhong Park, Jae W. Lee

ICML 2024 Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs Yeonhong Park, Jake Hyun, Sanglyul Cho, Bonggeun Sim, Jae W. Lee

ECCV 2024 Frugal 3D Point Cloud Model Training via Progressive near Point Filtering and Fused Aggregation Donghyun Lee, Yejin Lee, Jae W. Lee, Hongil Yoon

AAAI 2023 Not All Neighbors Matter: Point Distribution-Aware Pruning for 3D Point Cloud Yejin Lee, Donghyun Lee, JungUk Hong, Jae W. Lee, Hongil Yoon

ECCV 2022 L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training Jonghyun Bae, Woohyeon Baek, Tae Jun Ham, Jae W. Lee