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ORCIDByeongwook Kim
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2020 – today
- 2024
[c9]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- [c8]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 - [i17]Sunghyeon Woo, Baeseong Park, Byeongwook Kim, Minjung Jo, Sejung Kwon, Dongsuk Jeon, Dongsoo Lee:
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation. CoRR abs/2402.17812 (2024) - [i16]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) - [i15]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) - 2023
- [c7]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 - [i14]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
- [c6]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 - [c5]Baeseong Park, Se Jung Kwon, Daehwan Oh, Byeongwook Kim, Dongsoo Lee:
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression. ICLR 2022 - [i13]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) - [i12]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
- [i11]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) - [i10]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) - [i9]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
- [c4]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 - [c3]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 - [c2]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun:
FleXOR: Trainable Fractional Quantization. NeurIPS 2020 - [c1]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 - [i8]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) - [i7]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun:
FleXOR: Trainable Fractional Quantization. CoRR abs/2009.04126 (2020) - [i6]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
- [i5]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Parichay Kapoor, Gu-Yeon Wei:
Network Pruning for Low-Rank Binary Indexing. CoRR abs/1905.05686 (2019) - [i4]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) - [i3]Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Gu-Yeon Wei:
Learning Low-Rank Approximation for CNNs. CoRR abs/1905.10145 (2019) - 2018
- [i2]Dongsoo Lee, Byeongwook Kim:
Retraining-Based Iterative Weight Quantization for Deep Neural Networks. CoRR abs/1805.11233 (2018) - [i1]Dongsoo Lee, Parichay Kapoor, Byeongwook Kim:
DeepTwist: Learning Model Compression via Occasional Weight Distortion. CoRR abs/1810.12823 (2018)
Coauthor Index
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last updated on 2024-08-08 19:17 CEST by the dblp team
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