Byeongwook Kim

34 papers A* 8A 1Journal 22Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	An Investigation of FP8 Across Accelerators for LLM Inference. CoRR JiWoo Kim, Joonhyung Lee, Gunho Park, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee, Youngjoo Lee
2025	J	`jnl`	AnyBCQ: Hardware Efficient Flexible Binary-Coded Quantization for Multi-Precision LLMs. CoRR Gunho Park, Jeongin Bae, Beomseok Kwon, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee
2025	J	`jnl`	CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMs. CoRR Gunho Park, Jeongin Bae, Byeongwook Kim, Baeseong Park, Jiwon Ryu, Hoseung Kim, Se Jung Kwon, Dongsoo Lee
2025	J	`jnl`	Faster Inference of LLMs using FP8 on the Intel Gaudi. CoRR Joonhyung Lee, Shmulik Markovich-Golan, Daniel Ohayon, Yair Hanani, Gunho Park, Byeongwook Kim, Asaf Karnieli, Uri Livne, Haihao Shen, Tai Huang, Se Jung Kwon, Dongsoo Lee
2025	A*	`conf`	Secure Data Analytics in Apache Spark with Fine-grained Policy Enforcement and Isolated Execution. NDSS Byeongwook Kim, Jaewon Hur, Adil Ahmad, Byoungyoung Lee
2025	—	`conf`	Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models. ACL (1) Seungcheol Park, Jeongin Bae, Beomseok Kwon, Minjun Kim, Byeongwook Kim, Se Jung Kwon, U Kang, Dongsoo Lee
2025	J	`jnl`	Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models. CoRR Seungcheol Park, Jeongin Bae, Beomseok Kwon, Minjun Kim, Byeongwook Kim, Se Jung Kwon, U Kang, Dongsoo Lee
2024	A*	`conf`	DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation. NeurIPS Sunghyeon Woo, Baeseong Park, Byeongwook Kim, Minjung Jo, Se Jung Kwon, Dongsuk Jeon, Dongsoo Lee
2024	J	`jnl`	DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation. CoRR Sunghyeon Woo, Baeseong Park, Byeongwook Kim, Minjung Jo, Sejung Kwon, Dongsuk Jeon, Dongsoo Lee
2024	A*	`conf`	LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models. ICLR Gunho Park, Baeseong Park, Minsub Kim, Sungjae Lee, Jeonghoon Kim, Beomseok Kwon, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, Dongsoo Lee
2024	J	`jnl`	No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization. CoRR June Yong Yang, Byeongwook Kim, Jeongin Bae, Beomseok Kwon, Gunho Park, Eunho Yang, Se Jung Kwon, Dongsoo Lee
2024	A*	`conf`	Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models. ICLR Jung Hwan Heo, Jeonghoon Kim, Beomseok Kwon, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee
2024	J	`jnl`	To FP8 and Back Again: Quantifying the Effects of Reducing Precision on LLM Training Stability. CoRR Joonhyung Lee, Jeongin Bae, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee
2023	J	`jnl`	Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models. CoRR Jung Hwan Heo, Jeonghoon Kim, Beomseok Kwon, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee
2023	A*	`conf`	Winning Both the Accuracy of Floating Point Activation and the Simplicity of Integer Arithmetic. ICLR Yulhwa Kim, Jaeyong Jang, Jehun Lee, Jihoon Park, Jeonghoon Kim, Byeongwook Kim, Baeseong Park, Se Jung Kwon, Dongsoo Lee, Jae-Joon Kim
2022	—	`conf`	AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models. EMNLP (Findings) Se Jung Kwon, Jeonghoon Kim, Jeongin Bae, Kang Min Yoo, Jin-Hwa Kim, Baeseong Park, Byeongwook Kim, Jung-Woo Ha, Nako Sung, Dongsoo Lee
2022	J	`jnl`	AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models. CoRR Se Jung Kwon, Jeonghoon Kim, Jeongin Bae, Kang Min Yoo, Jin-Hwa Kim, Baeseong Park, Byeongwook Kim, Jung-Woo Ha, Nako Sung, Dongsoo Lee
2022	A*	`conf`	Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression. ICLR Baeseong Park, Se Jung Kwon, Daehwan Oh, Byeongwook Kim, Dongsoo Lee
2022	J	`jnl`	nuQmm: Quantized MatMul for Efficient Inference of Large-Scale Generative Language Models. CoRR Gunho Park, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, Dongsoo Lee
2021	J	`jnl`	Modulating Regularization Frequency for Efficient Compression-Aware Model Training. CoRR Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Baeseong Park, Yongkweon Jeon
2021	J	`jnl`	Q-Rater: Non-Convex Optimization for Post-Training Uniform Quantization. CoRR Byeongwook Kim, Dongsoo Lee, Yeonju Ro, Yongkweon Jeon, Se Jung Kwon, Baeseong Park, Daehwan Oh
2021	J	`jnl`	Sequential Encryption of Sparse Neural Networks Toward Optimum Representation of Irregular Sparsity. CoRR Baeseong Park, Se Jung Kwon, Dongsoo Lee, Daehwan Oh, Byeongwook Kim, Yongkweon Jeon, Yeonju Ro
2020	J	`jnl`	BiQGEMM: Matrix Multiplication with Lookup Table For Binary-Coding-based Quantized DNNs. CoRR Yongkweon Jeon, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Dongsoo Lee
2020	A	`conf`	BiQGEMM: matrix multiplication with lookup table for binary-coding-based quantized DNNs. SC Yongkweon Jeon, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Dongsoo Lee
2020	—	`conf`	Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation. EMNLP (Findings) Insoo Chung, Byeongwook Kim, Yoonjung Choi, Se Jung Kwon, Yongkweon Jeon, Baeseong Park, Sangha Kim, Dongsoo Lee
2020	J	`jnl`	Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation. CoRR Insoo Chung, Byeongwook Kim, Yoonjung Choi, Se Jung Kwon, Yongkweon Jeon, Baeseong Park, Sangha Kim, Dongsoo Lee
2020	A*	`conf`	FleXOR: Trainable Fractional Quantization. NeurIPS Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun
2020	J	`jnl`	FleXOR: Trainable Fractional Quantization. CoRR Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun
2020	A*	`conf`	Structured Compression by Weight Encryption for Unstructured Pruning and Quantization. CVPR Se Jung Kwon, Dongsoo Lee, Byeongwook Kim, Parichay Kapoor, Baeseong Park, Gu-Yeon Wei
2019	J	`jnl`	Learning Low-Rank Approximation for CNNs. CoRR Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Gu-Yeon Wei
2019	J	`jnl`	Network Pruning for Low-Rank Binary Indexing. CoRR Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Parichay Kapoor, Gu-Yeon Wei
2019	J	`jnl`	Structured Compression by Unstructured Pruning for Sparse Quantized Neural Networks. CoRR Se Jung Kwon, Dongsoo Lee, Byeongwook Kim, Parichay Kapoor, Baeseong Park, Gu-Yeon Wei
2018	J	`jnl`	DeepTwist: Learning Model Compression via Occasional Weight Distortion. CoRR Dongsoo Lee, Parichay Kapoor, Byeongwook Kim
2018	J	`jnl`	Retraining-Based Iterative Weight Quantization for Deep Neural Networks. CoRR Dongsoo Lee, Byeongwook Kim