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2020 – today
- 2024
[c18]Jung Hwan Heo, Jeonghoon Kim, Beomseok Kwon, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee:
Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models. ICLR 2024- [c17]Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-Chul Moon:
Label-Noise Robust Diffusion Models. ICLR 2024 - [c16]Gunho Park, Baeseong Park, Minsub Kim, Sungjae Lee, Jeonghoon Kim, Beomseok Kwon, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, Dongsoo Lee:
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models. ICLR 2024 - [i20]Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-Chul Moon:
Label-Noise Robust Diffusion Models. CoRR abs/2402.17517 (2024) - [i19]June Yong Yang, Byeongwook Kim, Jeongin Bae, Beomseok Kwon, Gunho Park, Eunho Yang, Se Jung Kwon, Dongsoo Lee:
No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization. CoRR abs/2402.18096 (2024) - [i18]Kang Min Yoo, Jaegeun Han, Sookyo In, Heewon Jeon, Jisu Jeong, Jaewook Kang, Hyunwook Kim, Kyung-Min Kim, Munhyong Kim, Sungju Kim, Donghyun Kwak, Hanock Kwak, Se Jung Kwon, Bado Lee, Dongsoo Lee, Gichang Lee, Jooho Lee, Baeseong Park, Seongjin Shin, Joonsang Yu, Seolki Baek, Sumin Byeon, Eungsup Cho, Dooseok Choe, Jeeseung Han, Youngkyun Jin, Hyein Jun, Jaeseung Jung, Chanwoong Kim, Jinhong Kim, Jinuk Kim, Dokyeong Lee, Dong Wook Park, Jeong Min Sohn, Sujung Han, Jiae Heo, Sungju Hong, Mina Jeon, Hyunhoon Jung, Jungeun Jung, Wangkyo Jung, Chungjoon Kim, Hyeri Kim, Jonghyun Kim, Min Young Kim, Soeun Lee, Joonhee Park, Jieun Shin, Sojin Yang, Jungsoon Yoon, Hwaran Lee, Sanghwan Bae, Jeehwan Cha, Karl Gylleus, Donghoon Ham, Mihak Hong, Youngki Hong, Yunki Hong, Dahyun Jang, Hyojun Jeon, Yujin Jeon, Yeji Jeong, Myunggeun Ji, Yeguk Jin, Chansong Jo, Shinyoung Joo, Seunghwan Jung, Adrian Jungmyung Kim, Byoung Hoon Kim, Hyomin Kim, Jungwhan Kim, Minkyoung Kim, Minseung Kim, Sungdong Kim, Yonghee Kim, Youngjun Kim, Youngkwan Kim, Donghyeon Ko, Dughyun Lee, Hayoung Lee, Jaehong Lee, Jieun Lee, Jonghyun Lee, Jongjin Lee, Min Young Lee, Yehbin Lee, Taehong Min, Yuri Min, Kiyoon Moon, Hyangnam Oh, Jaesun Park, Kyuyon Park, Younghun Park, Hanbae Seo, Seunghyun Seo, Mihyun Sim, Gyubin Son, Matt Yeo, Kyung Hoon Yeom, Wonjoon Yoo:
HyperCLOVA X Technical Report. CoRR abs/2404.01954 (2024) - [i17]Joonhyung Lee, Jeongin Bae, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee:
To FP8 and Back Again: Quantifying the Effects of Reducing Precision on LLM Training Stability. CoRR abs/2405.18710 (2024) - [i16]Jung Hyun Lee, Jeonghoon Kim, June Yong Yang, Se Jung Kwon, Eunho Yang, Kang Min Yoo, Dongsoo Lee:
LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices. CoRR abs/2407.11534 (2024) - 2023
- [c15]Eunji Yoo, Gunho Park, Jung Gyu Min, Se Jung Kwon, Baeseong Park, Dongsoo Lee, Youngjoo Lee:
TF-MVP: Novel Sparsity-Aware Transformer Accelerator with Mixed-Length Vector Pruning. DAC 2023: 1-6 - [c14]Yulhwa Kim, Jaeyong Jang, Jehun Lee, Jihoon Park, Jeonghoon Kim, Byeongwook Kim, Baeseong Park, Se Jung Kwon, Dongsoo Lee, Jae-Joon Kim:
Winning Both the Accuracy of Floating Point Activation and the Simplicity of Integer Arithmetic. ICLR 2023 - [c13]Dongjun Kim, Yeongmin Kim, Se Jung Kwon, Wanmo Kang, Il-Chul Moon:
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models. ICML 2023: 16567-16598 - [c12]Jung Hyun Lee, Jeonghoon Kim, Se Jung Kwon, Dongsoo Lee:
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization. ICML 2023: 18913-18939 - [c11]Younghoon Byun, Seungsik Moon, Baeseong Park, Se Jung Kwon, Dongsoo Lee, Gunho Park, Eunji Yoo, Jung Gyu Min, Youngjoo Lee:
Sparsity-Aware Memory Interface Architecture using Stacked XORNet Compression for Accelerating Pruned-DNN Models. MLSys 2023 - [c10]Jeonghoon Kim, Jung Hyun Lee, Sungdong Kim, Joonsuk Park, Kang Min Yoo, Se Jung Kwon, Dongsoo Lee:
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization. NeurIPS 2023 - [i15]Jeonghoon Kim
, Jung Hyun Lee, Sungdong Kim, Joonsuk Park, Kang Min Yoo, Se Jung Kwon, Dongsoo Lee:
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization. CoRR abs/2305.14152 (2023) - [i14]Jung Hyun Lee, Jeonghoon Kim, Se Jung Kwon, Dongsoo Lee:
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization. CoRR abs/2306.00317 (2023) - [i13]Jung Hwan Heo, Jeonghoon Kim, Beomseok Kwon, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee:
Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models. CoRR abs/2309.15531 (2023) - 2022
- [c9]Se Jung Kwon, Jeonghoon Kim, Jeongin Bae, Kang Min Yoo, Jin-Hwa Kim, Baeseong Park, Byeongwook Kim, Jung-Woo Ha, Nako Sung, Dongsoo Lee:
AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models. EMNLP (Findings) 2022: 3288-3305 - [c8]Baeseong Park, Se Jung Kwon, Daehwan Oh, Byeongwook Kim, Dongsoo Lee:
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression. ICLR 2022 - [c7]Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul Moon:
Maximum Likelihood Training of Implicit Nonlinear Diffusion Model. NeurIPS 2022 - [i12]Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul Moon:
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models. CoRR abs/2205.13699 (2022) - [i11]Gunho Park, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, Dongsoo Lee:
nuQmm: Quantized MatMul for Efficient Inference of Large-Scale Generative Language Models. CoRR abs/2206.09557 (2022) - [i10]Se Jung Kwon, Jeonghoon Kim, Jeongin Bae, Kang Min Yoo, Jin-Hwa Kim, Baeseong Park, Byeongwook Kim, Jung-Woo Ha, Nako Sung, Dongsoo Lee:
AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models. CoRR abs/2210.03858 (2022) - 2021
- [i9]Byeongwook Kim, Dongsoo Lee, Yeonju Ro, Yongkweon Jeon, Se Jung Kwon, Baeseong Park, Daehwan Oh:
Q-Rater: Non-Convex Optimization for Post-Training Uniform Quantization. CoRR abs/2105.01868 (2021) - [i8]Baeseong Park, Se Jung Kwon, Dongsoo Lee, Daehwan Oh, Byeongwook Kim, Yongkweon Jeon, Yeonju Ro:
Sequential Encryption of Sparse Neural Networks Toward Optimum Representation of Irregular Sparsity. CoRR abs/2105.01869 (2021) - [i7]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Baeseong Park, Yongkweon Jeon:
Modulating Regularization Frequency for Efficient Compression-Aware Model Training. CoRR abs/2105.01875 (2021) - 2020
- [j2]Se Jung Kwon, Bong Gu Kang, Changbeom Choi, Tag Gon Kim:
Adaptive Discrete Event Simulation Systems to Embrace Changes of Requirements Using Event Control Models. IEEE Trans. Syst. Man Cybern. Syst. 50(3): 1147-1160 (2020) - [c6]Se Jung Kwon, Dongsoo Lee, Byeongwook Kim, Parichay Kapoor, Baeseong Park, Gu-Yeon Wei:
Structured Compression by Weight Encryption for Unstructured Pruning and Quantization. CVPR 2020: 1906-1915 - [c5]Insoo Chung, Byeongwook Kim, Yoonjung Choi, Se Jung Kwon, Yongkweon Jeon, Baeseong Park, Sangha Kim, Dongsoo Lee:
Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation. EMNLP (Findings) 2020: 4812-4826 - [c4]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun:
FleXOR: Trainable Fractional Quantization. NeurIPS 2020 - [c3]Yongkweon Jeon, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Dongsoo Lee:
BiQGEMM: matrix multiplication with lookup table for binary-coding-based quantized DNNs. SC 2020: 95 - [i6]Yongkweon Jeon, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Dongsoo Lee:
BiQGEMM: Matrix Multiplication with Lookup Table For Binary-Coding-based Quantized DNNs. CoRR abs/2005.09904 (2020) - [i5]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun:
FleXOR: Trainable Fractional Quantization. CoRR abs/2009.04126 (2020) - [i4]Insoo Chung, Byeongwook Kim, Yoonjung Choi, Se Jung Kwon, Yongkweon Jeon, Baeseong Park, Sangha Kim, Dongsoo Lee:
Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation. CoRR abs/2009.07453 (2020)
2010 – 2019
- 2019
- [i3]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Parichay Kapoor, Gu-Yeon Wei:
Network Pruning for Low-Rank Binary Indexing. CoRR abs/1905.05686 (2019) - [i2]Se Jung Kwon, Dongsoo Lee, Byeongwook Kim, Parichay Kapoor, Baeseong Park, Gu-Yeon Wei:
Structured Compression by Unstructured Pruning for Sparse Quantized Neural Networks. CoRR abs/1905.10138 (2019) - [i1]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Gu-Yeon Wei:
Learning Low-Rank Approximation for CNNs. CoRR abs/1905.10145 (2019) - 2018
- [j1]Bong Gu Kang, Seon Han Choi, Se Jung Kwon, Jun Hee Lee, Tag Gon Kim:
Simulation-Based Optimization on the System-of-Systems Model via Model Transformation and Genetic Algorithm: A Case Study of Network-Centric Warfare. Complex. 2018: 4521672:1-4521672:15 (2018) - 2013
- [c2]Se Jung Kwon, Changho Sung, Hae Sang Song, Tag Gon Kim:
Integrated hybrid systems modeling and simulation methodology based on HDEVS formalism. SummerSim 2013: 52 - 2012
- [c1]Se Jung Kwon, Tag Gon Kim:
Design and implementation of event-based DEVS execution environment for faster execution of iterative simulation. SpringSim (TMS-DEVS) 2012: 14
Coauthor Index
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last updated on 2024-08-25 19:13 CEST by the dblp team
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