FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling. - Chang-Min Kim; Hyung-Min Park; Taesu Kim; Yoon-Kyung Choi; Soo-Young Lee (IEEE Trans. Neural Networks, 2003)

Modeling Auditory Pathway for Intelligent Information Acquisition. - Hyung-Min Park; Jong-Hwan Lee; Taesu Kim; Un-Min Bae; Byung Taek Kim; Ki-Young Park; Chang-Min Kim; Soo-Young Lee (Int. J. Inf. Acquis., 2004)

Robust time delay estimation in noisy reverberant environments with a probabilistic graphical model. - Taesu Kim; Hagai Attias; Soo-Young Lee; Te-Won Lee (ICASSP (5), 2005)

Learning self-organized topology-preserving complex speech features at primary auditory cortex. - Taesu Kim; Soo-Young Lee (Neurocomputing, 2005)

Multivariate Scale Mixture of Gaussians Modeling. - Torbjørn Eltoft; Taesu Kim; Te-Won Lee (ICA, 2006)

Independent Vector Analysis: An Extension of ICA to Multivariate Components. - Taesu Kim; Torbjørn Eltoft; Te-Won Lee (ICA, 2006)

Complex FastIVA: A Robust Maximum Likelihood Approach of MICA for Convolutive BSS. - Intae Lee; Taesu Kim; Te-Won Lee (ICA, 2006)

Frequency Domain Blind Source Separation Exploiting Higher-Order Dependencies. - Taesu Kim; Hagai Attias; Soo-Young Lee; Te-Won Lee (ICASSP (5), 2006)

On the multivariate Laplace distribution. - Torbjørn Eltoft; Taesu Kim; Te-Won Lee (IEEE Signal Process. Lett., 2006)

Independent Vector Analysis for Convolutive Blind Speech Separation. - Intae Lee; Taesu Kim; Te-Won Lee (Blind Speech Separation, 2007)

Robust Independent Component Analysis Using Quadratic Negentropy. - Jaehyung Lee 001; Taesu Kim; Soo-Young Lee (ICA, 2007)

Fast fixed-point independent vector analysis algorithms for convolutive blind source separation. - Intae Lee; Taesu Kim; Te-Won Lee (Signal Process., 2007)

Blind Source Separation Exploiting Higher-Order Frequency Dependencies. - Taesu Kim; Hagai Thomas Attias; Soo-Young Lee; Te-Won Lee (IEEE Trans. Speech Audio Process., 2007)

Binaural loudness based speech reinforcement with a closed-form solution. - Ho Seon Shin; Min-Seok Choi; Taesu Kim; Hong-Goo Kang (ICASSP, 2010)

Real-Time Independent Vector Analysis for Convolutive Blind Source Separation. - Taesu Kim (IEEE Trans. Circuits Syst. I Regul. Pap., 2010)

Self-similarity Based Lightweight Intrusion Detection Method for Cloud Computing. - Hyukmin Kwon; Taesu Kim; Song Jin Yu; Huy Kang Kim (ACIIDS (2), 2011)

Revisiting level-0 caches in embedded processors. - Nam Duong; Taesu Kim; Dali Zhao; Alexander V. Veidenbaum (CASES, 2012)

Improving Cache Management Policies Using Dynamic Reuse Distances. - Nam Duong; Dali Zhao; Taesu Kim; Rosario Cammarota; Mateo Valero; Alexander V. Veidenbaum (MICRO, 2012)

Multiple stream tracker: a new hardware stride prefetcher. - Taesu Kim; Dali Zhao; Alexander V. Veidenbaum (Conf. Computing Frontiers, 2014)

Speaker Clustering by Iteratively Finding Discriminative Feature Space and Cluster Labels. - Sungrack Yun; Hye Jin Jang; Taesu Kim (INTERSPEECH, 2017)

c.light: A Tool for Exploring Light Properties in Early Design Stage. - Kyeong-Ah Jeong; EunJin Kim; Taesu Kim; Hyeon-Jeong Suk (CHI, 2018)

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)

Voice Imitating Text-to-Speech Neural Networks. - Younggun Lee; Taesu Kim; Soo-Young Lee (CoRR, 2018)

Learning pronunciation from a foreign language in speech synthesis networks. - Younggun Lee; Taesu Kim (CoRR, 2018)

Deep Neural Network Optimized to Resistive Memory with Nonlinear Current-Voltage Characteristics. - Hyungjun Kim; Taesu Kim; Jinseok Kim 004; Jae-Joon Kim (ACM J. Emerg. Technol. Comput. Syst., 2018)

True White Point for Television Screens Across Different Viewing Conditions. - Kyungah Choi; Taesu Kim; Jeonghwan Chang; Hyeon-Jeong Suk (IEEE Trans. Consumer Electron., 2018)

Configurable BCAM/TCAM Based on 6T SRAM Bit Cell and Enhanced Match Line Clamping. - Jongeun Koo; Eunhwan Kim; Seunghyun Yoo; Taesu Kim; Sungju Ryu; Jae-Joon Kim (A-SSCC, 2019)

Robust and Fine-grained Prosody Control of End-to-end Speech Synthesis. - Younggun Lee; Taesu Kim (ICASSP, 2019)

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)

Illuminant Estimation Through Reverse Calibration of an Auto White-Balanced Image That Contains Displays. - Taesu Kim; EunJin Kim; Hyeon-Jeong Suk (CIC, 2019)

Large-Scale Speaker Retrieval on Random Speaker Variability Subspace. - Suwon Shon; Younggun Lee; Taesu Kim (INTERSPEECH, 2019)

Area-Efficient and Variation-Tolerant In-Memory BNN Computing using 6T SRAM Array. - Jinseok Kim 004; Jongeun Koo; Taesu Kim; Yulhwa Kim; Hyungjun Kim; Seunghyun Yoo; Jae-Joon Kim (VLSI Circuits, 2019)

A 44.1TOPS/W Precision-Scalable Accelerator for Quantized Neural Networks in 28nm CMOS. - Sungju Ryu; Hyungjun Kim; Wooseok Yi; Jongeun Koo; Eunhwan Kim; Yulhwa Kim; Taesu Kim; Jae-Joon Kim (CICC, 2020)

V-LSTM: An Efficient LSTM Accelerator Using Fixed Nonzero-Ratio Viterbi-Based Pruning. - Taesu Kim; Daehyun Ahn; Jae-Joon Kim (FPGA, 2020)

Time-step interleaved weight reuse for LSTM neural network computing. - Naebeom Park; Yulhwa Kim; Daehyun Ahn; Taesu Kim; Jae-Joon Kim (ISLPED, 2020)

SPRITE: Sparsity-Aware Neural Processing Unit with Constant Probability of Index-Matching. - Sungju Ryu; Youngtaek Oh; Taesu Kim; Daehyun Ahn; Jae-Joon Kim (DATE, 2021)

Pokemon color adjustments for augmented reality contents. - Donggun Lee; Taesu Kim; Hyeon-Jeong Suk (Color Imaging: Displaying, Processing, Hardcopy, and Applications, 2022)

GP22: A Car Styling Dataset for Automotive Designers. - Gyunpyo Lee; Taesu Kim; Hyeon-Jeong Suk (CVPR Workshops, 2022)

Text-driven Emotional Style Control and Cross-speaker Style Transfer in Neural TTS. - Yookyung Shin; Younggun Lee; Suhee Jo; Yeongtae Hwang; Taesu Kim (INTERSPEECH, 2022)

EdiTTS: Score-based Editing for Controllable Text-to-Speech. - Jaesung Tae; Hyeongju Kim; Taesu Kim (INTERSPEECH, 2022)

User Responses to Dynamic Light in Automobiles With EEG and Self-Assessments. - Taesu Kim; Gyunpyo Lee; Minjung Park; Hong Min Lee; Ji-Woo Park; Hyeon-Jeong Suk (IEEE Access, 2022)

Affective responses to chromatic ambient light in a vehicle. - Taesu Kim; Kyungah Choi; Hyeon-Jeong Suk (CoRR, 2022)

Hi, KIA: A Speech Emotion Recognition Dataset for Wake-Up Words. - Taesu Kim; Seungheon Doh; Gyunpyo Lee; Hyungseok Jeon; Juhan Nam; Hyeon-Jeong Suk (CoRR, 2022)

Sketching in-vehicle ambient lighting in virtual reality with the Wizard-of-Oz method. - Taesu Kim; Aigerim Shunayeva; Gyunpyo Lee; Hyeon-Jeong Suk (Digit. Creativity, 2022)

BitBlade: Energy-Efficient Variable Bit-Precision Hardware Accelerator for Quantized Neural Networks. - Sungju Ryu; Hyungjun Kim; Wooseok Yi; Eunhwan Kim; Yulhwa Kim; Taesu Kim; Jae-Joon Kim (IEEE J. Solid State Circuits, 2022)

Affective Role of the Future Autonomous Vehicle Interior. - Taesu Kim; Gyunpyo Lee; Jiwoo Hong; Hyeon-Jeong Suk (AutomotiveUI (Adjunct Proceedings), 2023)

Cross-Speaker Emotion Transfer by Manipulating Speech Style Latents. - Suhee Jo; Younggun Lee; Yookyung Shin; Yeongtae Hwang; Taesu Kim (ICASSP, 2023)

Leveraging Early-Stage Robustness in Diffusion Models for Efficient and High-Quality Image Synthesis. - Yulhwa Kim; Dongwon Jo; Hyesung Jeon; Taesu Kim; Daehyun Ahn; Hyungjun Kim; Jae-Joon Kim (NeurIPS, 2023)

Searching for Robust Binary Neural Networks via Bimodal Parameter Perturbation. - Daehyun Ahn; Hyungjun Kim; Taesu Kim; Eunhyeok Park; Jae-Joon Kim (WACV, 2023)

OWQ: Lessons learned from activation outliers for weight quantization in large language models. - Changhun Lee; Jungyu Jin; Taesu Kim; Hyungjun Kim; Eunhyeok Park (CoRR, 2023)

Squeezing Large-Scale Diffusion Models for Mobile. - Jiwoong Choi; Minkyu Kim; Daehyun Ahn; Taesu Kim; Yulhwa Kim; Dongwon Jo; Hyesung Jeon; Jae-Joon Kim; Hyungjun Kim (CoRR, 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)

OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models. - Changhun Lee; Jungyu Jin; Taesu Kim; Hyungjun Kim; Eunhyeok Park (AAAI, 2024)

VR-SSVEPeripheral: Designing Virtual Reality Friendly SSVEP Stimuli using Peripheral Vision Area for Immersive and Comfortable Experience. - Jinwook Kim; Taesu Kim; Jeongmi Lee (CHI Extended Abstracts, 2024)

SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks. - Jiwon Song; Kyungseok Oh; Taesu Kim; Hyungjun Kim; Yulhwa Kim; Jae-Joon Kim (ICML, 2024)

Mixture of Scales: Memory-Efficient Token-Adaptive Binarization for Large Language Models. - Dongwon Jo; Taesu Kim; Yulhwa Kim; Jae-Joon Kim (NeurIPS, 2024)

QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference. - Taesu Kim; Jongho Lee; Daehyun Ahn; Sarang Kim; Jiwoong Choi; Minkyu Kim; Hyungjun Kim (CoRR, 2024)

Music Discovery Dialogue Generation Using Human Intent Analysis and Large Language Models. - Seungheon Doh; Keunwoo Choi; Daeyong Kwon; Taesu Kim; Juhan Nam (CoRR, 2024)

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)

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)

GraLoRA: Granular Low-Rank Adaptation for Parameter-Efficient Fine-Tuning. - Yeonjoon Jung; Daehyun Ahn; Hyungjun Kim; Taesu Kim; Eunhyeok Park (CoRR, 2025)