Column-selection-enabled 8T SRAM array with 1R/1W multi-port operation for DVFS-enabled processors. - Sang Phill Park; Soo Youn Kim; Dongsoo Lee; Jae-Joon Kim; W. Paul Griffin; Kaushik Roy 001 (ISLPED, 2011)

Memory-based embedded digital ATE. - Dongsoo Lee; Sang Phill Park; Ashish Goel; Kaushik Roy 001 (VTS, 2011)

High-performance low-energy STT MRAM based on balanced write scheme. - Dongsoo Lee; Sumeet Kumar Gupta; Kaushik Roy 001 (ISLPED, 2012)

Viterbi-Based Efficient Test Data Compression. - Dongsoo Lee; Kaushik Roy 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2012)

Soft-Error-Resilient FPGAs Using Built-In 2-D Hamming Product Code. - Sang Phill Park; Dongsoo Lee; Kaushik Roy 001 (IEEE Trans. Very Large Scale Integr. Syst., 2012)

Fast management of ONUs based on broadcast control channel for a 10-gigabit-capable passive optical network (XG-PON) system. - Youngsuk Lee; Dongsoo Lee; Hark Yoo; Youngsun Kim; Younghan Kim 002 (J. Commun. Networks, 2013)

Area Efficient ROM-Embedded SRAM Cache. - Dongsoo Lee; Kaushik Roy 001 (IEEE Trans. Very Large Scale Integr. Syst., 2013)

Design and Optimization of Multiple-Mesh Clock Network. - Jinwook Jung; Dongsoo Lee; Youngsoo Shin (VLSI-SoC (Selected Papers), 2014)

Optimal wavelength provisioning with fuzzy logic control for power saving in TWDM-PONs. - Hark Yoo; Dongsoo Lee; Man-Soo Han (ICTC, 2016)

Embedding Read-Only Memory in Spin-Transfer Torque MRAM-Based On-Chip Caches. - Xuanyao Fong; Rangharajan Venkatesan; Dongsoo Lee; Anand Raghunathan; Kaushik Roy 001 (IEEE Trans. Very Large Scale Integr. Syst., 2016)

Forward Secure Dynamic Searchable Symmetric Encryption with Efficient Updates. - Kee Sung Kim; Minkyu Kim; Dongsoo Lee; Je Hong Park; Woo-Hwan Kim (CCS, 2017)

Security of Stateful Order-Preserving Encryption. - Kee Sung Kim; Minkyu Kim; Dongsoo Lee; Je Hong Park; Woo-Hwan Kim (ICISC, 2017)

Viterbi-based Pruning for Sparse Matrix with Fixed and High Index Compression Ratio. - Dongsoo Lee; Daehyun Ahn; Taesu Kim; Pierce I-Jen Chuang; Jae-Joon Kim (ICLR (Poster), 2018)

Across the Stack Opportunities for Deep Learning Acceleration. - Vijayalakshmi Srinivasan; Bruce M. Fleischer; Sunil Shukla; Matthew M. Ziegler; Joel Silberman; Jinwook Oh; Jungwook Choi; Silvia M. Mueller; Ankur Agrawal; Tina Babinsky; Nianzheng Cao; Chia-Yu Chen; et al. (ISLPED, 2018)

A Scalable Multi- TeraOPS Deep Learning Processor Core for AI Trainina and Inference. - Bruce M. Fleischer; Sunil Shukla; Matthew M. Ziegler; Joel Silberman; Jinwook Oh; Vijayalakshmi Srinivasan; Jungwook Choi; Silvia M. Mueller; Ankur Agrawal; Tina Babinsky; Nianzheng Cao; Chia-Yu Chen; et al. (VLSI Circuits, 2018)

Retraining-Based Iterative Weight Quantization for Deep Neural Networks. - Dongsoo Lee; Byeongwook Kim (CoRR, 2018)

DeepTwist: Learning Model Compression via Occasional Weight Distortion. - Dongsoo Lee; Parichay Kapoor; Byeongwook Kim (CoRR, 2018)

Double Viterbi: Weight Encoding for High Compression Ratio and Fast On-Chip Reconstruction for Deep Neural Network. - Daehyun Ahn; Dongsoo Lee; Taesu Kim; Jae-Joon Kim (ICLR (Poster), 2019)

Network Pruning for Low-Rank Binary Indexing. - Dongsoo Lee; Se Jung Kwon; Byeongwook Kim; Parichay Kapoor; Gu-Yeon Wei (CoRR, 2019)

Structured Compression by Unstructured Pruning for Sparse Quantized Neural Networks. - Se Jung Kwon; Dongsoo Lee; Byeongwook Kim; Parichay Kapoor; Baeseong Park; Gu-Yeon Wei (CoRR, 2019)

Learning Low-Rank Approximation for CNNs. - Dongsoo Lee; Se Jung Kwon; Byeongwook Kim; Gu-Yeon Wei (CoRR, 2019)

A Review of On-Device Fully Neural End-to-End Automatic Speech Recognition Algorithms. - Chanwoo Kim 001; Dhananjaya Gowda; Dongsoo Lee; Jiyeon Kim; Ankur Kumar; Sungsoo Kim; Abhinav Garg; Changwoo Han (ACSSC, 2020)

Structured Compression by Weight Encryption for Unstructured Pruning and Quantization. - Se Jung Kwon; Dongsoo Lee; Byeongwook Kim; Parichay Kapoor; Baeseong Park; Gu-Yeon Wei (CVPR, 2020)

Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation. - Insoo Chung; Byeongwook Kim; Yoonjung Choi; Se Jung Kwon; Yongkweon Jeon; Baeseong Park; Sangha Kim 002; Dongsoo Lee (EMNLP (Findings), 2020)

FleXOR: Trainable Fractional Quantization. - Dongsoo Lee; Se Jung Kwon; Byeongwook Kim; Yongkweon Jeon; Baeseong Park; Jeongin Yun (NeurIPS, 2020)

BiQGEMM: matrix multiplication with lookup table for binary-coding-based quantized DNNs. - Yongkweon Jeon; Baeseong Park; Se Jung Kwon; Byeongwook Kim; Jeongin Yun; Dongsoo Lee (SC, 2020)

A mechanistically interpretable model of the retinal neural code for natural scenes with multiscale adaptive dynamics. - Xuehao Ding; Dongsoo Lee; Satchel Grant; Heike Stein; Lane McIntosh; Niru Maheswaranathan; Stephen Baccus (ACSCC, 2021)

Q-Rater: Non-Convex Optimization for Post-Training Uniform Quantization. - Byeongwook Kim; Dongsoo Lee; Yeonju Ro; Yongkweon Jeon; Se Jung Kwon; Baeseong Park; Daehwan Oh (CoRR, 2021)

Sequential Encryption of Sparse Neural Networks Toward Optimum Representation of Irregular Sparsity. - Baeseong Park; Se Jung Kwon; Dongsoo Lee; Daehwan Oh; Byeongwook Kim; Yongkweon Jeon; Yeonju Ro (CoRR, 2021)

Modulating Regularization Frequency for Efficient Compression-Aware Model Training. - Dongsoo Lee; Se Jung Kwon; Byeongwook Kim; Jeongin Yun; Baeseong Park; Yongkweon Jeon (CoRR, 2021)

AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models. - Se Jung Kwon; Jeonghoon Kim; Jeongin Bae; Kang Min Yoo; Jin-Hwa Kim; Baeseong Park; Byeongwook Kim; Jung-Woo Ha 001; Nako Sung; Dongsoo Lee (EMNLP (Findings), 2022)

DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation. - Seongmin Hong; Seungjae Moon; Junsoo Kim 002; Sungjae Lee 002; Minsub Kim; Dongsoo Lee; Joo-Young Kim 001 (HCS, 2022)

Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression. - Baeseong Park; Se Jung Kwon; Daehwan Oh; Byeongwook Kim; Dongsoo Lee (ICLR, 2022)

Volume is All You Need: Improving Multi-task Multiple Instance Learning for WMH Segmentation and Severity Estimation. - Wooseok Jung; Chong Hyun Suh; Woo-Hyun Shim; Jinyoung Kim; Dongsoo Lee; Changhyun Park; Seo Taek Kong; Kyu-Hwan Jung; Hwon Heo; Sang Joon Kim (MLCN@MICCAI, 2022)

Augmenting Magnetic Resonance Imaging with Tabular Features for Enhanced and Interpretable Medial Temporal Lobe Atrophy Prediction. - Dongsoo Lee; Chong Hyun Suh; Jinyoung Kim; Wooseok Jung; Changhyun Park; Kyu-Hwan Jung; Seo Taek Kong; Woo-Hyun Shim; Hwon Heo; Sang Joon Kim (MLCN@MICCAI, 2022)

Maximum Likelihood Training of Implicit Nonlinear Diffusion Model. - Dongjun Kim; Byeonghu Na; Se Jung Kwon; Dongsoo Lee; Wanmo Kang; Il-Chul Moon (NeurIPS, 2022)

Maximum Likelihood Training of Implicit Nonlinear Diffusion Models. - Dongjun Kim; Byeonghu Na; Se Jung Kwon; Dongsoo Lee; Wanmo Kang; Il-Chul Moon (CoRR, 2022)

nuQmm: Quantized MatMul for Efficient Inference of Large-Scale Generative Language Models. - Gunho Park; Baeseong Park; Se Jung Kwon; Byeongwook Kim; Youngjoo Lee; Dongsoo Lee (CoRR, 2022)

TF-MVP: Novel Sparsity-Aware Transformer Accelerator with Mixed-Length Vector Pruning. - Eunji Yoo; Gunho Park; Jung Gyu Min; Se Jung Kwon; Baeseong Park; Dongsoo Lee; Youngjoo Lee (DAC, 2023)

Winning Both the Accuracy of Floating Point Activation and the Simplicity of Integer Arithmetic. - Yulhwa Kim; Jaeyong Jang; Jehun Lee; Jihoon Park; Jeonghoon Kim; Byeongwook Kim; Baeseong Park; Se Jung Kwon; Dongsoo Lee; Jae-Joon Kim (ICLR, 2023)

FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization. - Jung Hyun Lee; Jeonghoon Kim; Se Jung Kwon; Dongsoo Lee (ICML, 2023)

Sparsity-Aware Memory Interface Architecture using Stacked XORNet Compression for Accelerating Pruned-DNN Models. - Younghoon Byun; Seungsik Moon; Baeseong Park; Se Jung Kwon; Dongsoo Lee; Gunho Park; Eunji Yoo; Jung Gyu Min; Youngjoo Lee (MLSys, 2023)

Information Geometry of the Retinal Representation Manifold. - Xuehao Ding; Dongsoo Lee; Joshua Melander; George Sivulka; Surya Ganguli; Stephen Baccus (NeurIPS, 2023)

Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization. - Jeonghoon Kim; Jung Hyun Lee; Sungdong Kim; Joonsuk Park; Kang Min Yoo; Se Jung Kwon; Dongsoo Lee (NeurIPS, 2023)

Fully Parallel, One-Cycle Random Shuffling for Efficient Countermeasure in Post-Quantum Cryptography. - Jong-Yeon Park; Dongsoo Lee; Seonggyeom Kim; Wonil Lee; Bo-Gyeong Kang; Kouichi Sakurai (IACR Cryptol. ePrint Arch., 2023)

Machine learning-based quantification for disease uncertainty increases the statistical power of genetic association studies. - Jun Young Park; Jang Jae Lee; Younghwa Lee; Dongsoo Lee; Jungsoo Gim; Lindsay A. Farrer; Kun Ho Lee; Sungho Won (Bioinform., 2023)

V-LSTM: An Efficient LSTM Accelerator Using Fixed Nonzero-Ratio Viterbi-Based Pruning. - Taesu Kim; Daehyun Ahn; Dongsoo Lee; Jae-Joon Kim (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models. - Jung Hwan Heo; Jeonghoon Kim; Beomseok Kwon; Byeongwook Kim; Se Jung Kwon; Dongsoo Lee (ICLR, 2024)

LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models. - Gunho Park; Baeseong Park; Minsub Kim; Sungjae Lee 002; Jeonghoon Kim; Beomseok Kwon; Se Jung Kwon; Byeongwook Kim; Youngjoo Lee; Dongsoo Lee (ICLR, 2024)

32.2 A 24.25-to-29.5GHz Extremely Compact Doherty Power Amplifier with Differential-Breaking Phase Offset Achieving 23.7% PAEavg for 5G Base-Station Transceivers. - Hansik Oh; Seungwon Park; Jooseok Lee; Seungjae Baek; Joonho Jung; Taewan Kim; Jinhyun Kim; Woojae Lee; Jae-Hong Park; Kihyun Kim; Dong-Hyun Lee; Sangho Lee; et al. (ISSCC, 2024)

DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation. - Sunghyeon Woo; Baeseong Park; Byeongwook Kim; Minjung Jo; Se Jung Kwon; Dongsuk Jeon; Dongsoo Lee (NeurIPS, 2024)

DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation. - Sunghyeon Woo; Baeseong Park; Byeongwook Kim; Minjung Jo; Sejung Kwon; Dongsuk Jeon; Dongsoo Lee (CoRR, 2024)

No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization. - June Yong Yang; Byeongwook Kim; Jeongin Bae; Beomseok Kwon; Gunho Park; Eunho Yang; Se Jung Kwon; Dongsoo Lee (CoRR, 2024)

HyperCLOVA X Technical Report. - 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; et al. (CoRR, 2024)

To FP8 and Back Again: Quantifying the Effects of Reducing Precision on LLM Training Stability. - Joonhyung Lee; Jeongin Bae; Byeongwook Kim; Se Jung Kwon; Dongsoo Lee (CoRR, 2024)

Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models. - Seungcheol Park; Jeongin Bae; Beomseok Kwon; Minjun Kim 010; Byeongwook Kim; Se Jung Kwon; U Kang; Dongsoo Lee (ACL (1), 2025)

FIGLUT: An Energy-Efficient Accelerator Design for FP-INT GEMM Using Look-Up Tables. - Gunho Park; Hyeokjun Kwon; Jiwoo Kim; Jeongin Bae; Baeseong Park; Dongsoo Lee; Youngjoo Lee (HPCA, 2025)

Debunking the CUDA Myth Towards GPU-based AI Systems: Evaluation of the Performance and Programmability of Intel's Gaudi NPU for AI Model Serving. - Yunjae Lee; Juntaek Lim; Jehyeon Bang; Eunyeong Cho; Huijong Jeong; Taesu Kim; Hyungjun Kim; Joonhyung Lee; Jinseop Im; Ranggi Hwang; Se Jung Kwon; Dongsoo Lee; et al. (ISCA, 2025)

5.4 A 22nm FDSOI CMOS-Based Compact 3-Stack Doherty Power Amplifier with a Stacked OPA-Based Bias Scheme Achieving >16.5dBm Pavg for 5G FR2 Applications. - Jooseok Lee; Hansik Oh; Seungjae Baek; Seungwon Park; Dongsoo Lee; Sehyug Jeon; Taewan Kim; Joonho Jung; Sung-Gi Yang (ISSCC, 2025)

LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices. - Jung Hyun Lee; Jeonghoon Kim; June Yong Yang; Se Jung Kwon; Eunho Yang; Kang Min Yoo; Dongsoo Lee (NAACL (Long Papers), 2025)

Debunking the CUDA Myth Towards GPU-based AI Systems. - Yunjae Lee; Juntaek Lim; Jehyeon Bang; Eunyeong Cho; Huijong Jeong; Taesu Kim; Hyungjun Kim; Joonhyung Lee; Jinseop Im; Ranggi Hwang; Se Jung Kwon; Dongsoo Lee; et al. (CoRR, 2025)

An Investigation of FP8 Across Accelerators for LLM Inference. - Jiwoo Kim; Joonhyung Lee; Gunho Park; Byeongwook Kim; Se Jung Kwon; Dongsoo Lee; Youngjoo Lee (CoRR, 2025)

Faster Inference of LLMs using FP8 on the Intel Gaudi. - 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 (CoRR, 2025)