Byeongwook Kim

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 26

Top Topics

Efficient Inference

Matrix Multiplication

Top Venues

EMNLP (Findings)

Publications

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)
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)
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 (2024)
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 (2024)
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 (2024)
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 (2023)
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)
Baeseong Park, Se Jung Kwon, Daehwan Oh, Byeongwook Kim, Dongsoo Lee
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression. ICLR (2022)
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 (2022)
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 (2022)
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)
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 (2021)
Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Baeseong Park, Yongkweon Jeon
Modulating Regularization Frequency for Efficient Compression-Aware Model Training. CoRR (2021)
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 (2021)
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 (2020)
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)
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 (2020)
Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun
FleXOR: Trainable Fractional Quantization. CoRR (2020)
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)
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)
Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun
FleXOR: Trainable Fractional Quantization. NeurIPS (2020)
Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Parichay Kapoor, Gu-Yeon Wei
Network Pruning for Low-Rank Binary Indexing. CoRR (2019)
Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Gu-Yeon Wei
Learning Low-Rank Approximation for CNNs. CoRR (2019)
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 (2019)
Dongsoo Lee, Parichay Kapoor, Byeongwook Kim
DeepTwist: Learning Model Compression via Occasional Weight Distortion. CoRR (2018)
Dongsoo Lee, Byeongwook Kim
Retraining-Based Iterative Weight Quantization for Deep Neural Networks. CoRR (2018)