Jungwook Choi
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
48
Venues
22
Active years
2006–2026
Best venue rank
A*
Where they publish
- MulticonferenceICASSP7 papers
- A*DAC5 papers
- BFPL4 papers
- A*AAAI3 papers
- A*ACL3 papers
- A*EMNLP3 papers
- AEACL2 papers
- A*HPCA2 papers
- A*ICCV2 papers
- A*MICRO2 papers
- A*ICLR2 papers
- A*ISCA2 papers
- AISLPED2 papers
- A*CVPR1 paper
- CARITH1 paper
- NationalHiPC1 paper
- ADATE1 paper
- AFPGA1 paper
- BISPASS1 paper
- CMEMOCODE1 paper
- A*MOBICOM1 paper
- AIROS1 paper
Papers
48 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | EACL | MapCoder-Lite: Distilling Multi-Agent Coding into a Single Small LLM. | Woongkyu Lee, Junhee Cho, Jungwook Choi |
| 2026 | HPCA | PIMphony: Overcoming Bandwidth and Capacity Inefficiency in PIM-Based Long-Context LLM Inference System. | Hyucksung Kwon, Kyungmo Koo, Janghyeon Kim, Woongkyu Lee, Minjae Lee, Gyeonggeun Jung, Hyungdeok Lee, Yousub Jung, Jaehan Park, Yosub Song, Byeongsu Yang, Haerang Choi, Guhyun Kim, Jongsoon Won, Woojae Shin, Changhyun Kim, Gyeongcheol Shin, Yongkee Kwon, Ilkon Kim, Euicheol Lim, John Kim, Jungwook Choi |
| 2025 | AAAI | RILQ: Rank-Insensitive LoRA-Based Quantization Error Compensation for Boosting 2-Bit Large Language Model Accuracy. | Geonho Lee, Janghwan Lee, Sukjin Hong, Minsoo Kim, Euijai Ahn, Du-Seong Chang, Jungwook Choi |
| 2025 | ACL | AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference. | Janghwan Lee, Jiwoong Park, Jinseok Kim, Yongjik Kim, Jungju Oh, Jinwook Oh, Jungwook Choi |
| 2025 | ICCV | Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control. | Seongmin Park, Hyungmin Kim, Sangwoo Kim, Wonseok Jeon, Juyoung Yang, Byeongwook Jeon, Yoonseon Oh, Jungwook Choi |
| 2025 | ICCV | Enhancing Generalization in Data-Free Quantization via Mixup-Class Prompting. | Jiwoong Park, Chaeun Lee, Yongseok Choi, Sein Park, Deokki Hong, Jungwook Choi |
| 2025 | MICRO | SkipReduce: (Interconnection) Network Sparsity to Accelerate Distributed Machine Learning. | Hans Kasan, Dennis Abts, Jungwook Choi, John Kim |
| 2024 | ACL | RA-LoRA: Rank-Adaptive Parameter-Efficient Fine-Tuning for Accurate 2-bit Quantized Large Language Models. | Minsoo Kim, Sihwa Lee, Wonyong Sung, Jungwook Choi |
| 2024 | ACL | Improving Conversational Abilities of Quantized Large Language Models via Direct Preference Alignment. | Janghwan Lee, Seongmin Park, Sukjin Hong, Minsoo Kim, Du-Seong Chang, Jungwook Choi |
| 2024 | CVPR | Selectively Dilated Convolution for Accuracy-Preserving Sparse Pillar-based Embedded 3D Object Detection. | Seongmin Park, Minjae Lee, Junwon Choi, Jungwook Choi |
| 2024 | EMNLP | InfiniPot: Infinite Context Processing on Memory-Constrained LLMs. | Minsoo Kim, Kyuhong Shim, Jungwook Choi, Simyung Chang |
| 2024 | HPCA | SPADE: Sparse Pillar-based 3D Object Detection Accelerator for Autonomous Driving. | Minjae Lee, Seongmin Park, Hyungmin Kim, Minyong Yoon, Janghwan Lee, Jun Won Choi, Nam Sung Kim, Mingu Kang, Jungwook Choi |
| 2024 | MICRO | BABOL: A Software-Defined NAND Flash Controller. | Kibin Park, Alberto Lerner, Sangjin Lee, Philippe Bonnet, Yong Ho Song, Philippe Cudr-Mauroux, Jungwook Choi |
| 2023 | DAC | Range-Invariant Approximation of Non-Linear Operations for Efficient BERT Fine-Tuning. | Janghyeon Kim, Janghwan Lee, Jungwook Choi, JeongHo Han, Sangheon Lee |
| 2023 | EACL | Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers. | Minsoo Kim, Kyuhong Shim, Seongmin Park, Wonyong Sung, Jungwook Choi |
| 2023 | EMNLP | Enhancing Computation Efficiency in Large Language Models through Weight and Activation Quantization. | Janghwan Lee, Minsoo Kim, Seungcheol Baek, Seok Joong Hwang, Wonyong Sung, Jungwook Choi |
| 2023 | ICASSP | Finding Optimal Numerical Format for Sub-8-Bit Post-Training Quantization of Vision Transformers. | Janghwan Lee, Youngdeok Hwang, Jungwook Choi |
| 2022 | DAC | NN-LUT: neural approximation of non-linear operations for efficient transformer inference. | Joonsang Yu, Junki Park, Seongmin Park, Minsoo Kim, Sihwa Lee, Dong Hyun Lee, Jungwook Choi |
| 2022 | EMNLP | Understanding and Improving Knowledge Distillation for Quantization Aware Training of Large Transformer Encoders. | Minsoo Kim, Sihwa Lee, Sukjin Hong, Du-Seong Chang, Jungwook Choi |
| 2022 | ICLR | Understanding the Role of Self Attention for Efficient Speech Recognition. | Kyuhong Shim, Jungwook Choi, Wonyong Sung |
| 2021 | AAAI | Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks. | Yoonho Boo, Sungho Shin, Jungwook Choi, Wonyong Sung |
| 2021 | ISCA | RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. | Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Wang, Sanchari Sen, Jintao Zhang, Ankur Agrawal, Monodeep Kar, Shubham Jain, Alberto Mannari, Hoang Tran, Yulong Li, Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Marcel Schaal, Mauricio J. Serrano, Jungwook Choi, Xiao Sun, Naigang Wang, Chia-Yu Chen, Allison Allain, James Bonanno, Nianzheng Cao, Robert Casatuta, Matthew Cohen, Bruce M. Fleischer, Michael Guillorn, Howard Haynie, Jinwook Jung, Mingu Kang, Kyu-Hyoun Kim, Siyu Koswatta, Sae Kyu Lee, Martin Lutz, Silvia M. Mueller, Jinwook Oh, Ashish Ranjan, Zhibin Ren, Scot Rider, Kerstin Schelm, Michael Scheuermann, Joel Silberman, Jie Yang, Vidhi Zalani, Xin Zhang, Ching Zhou, Matthew M. Ziegler, Vinay Shah, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan |
| 2019 | ARITH | DLFloat: A 16-b Floating Point Format Designed for Deep Learning Training and Inference. | Ankur Agrawal, Bruce M. Fleischer, Silvia M. Mueller, Xiao Sun, Naigang Wang, Jungwook Choi, Kailash Gopalakrishnan |
| 2019 | DAC | BiScaled-DNN: Quantizing Long-tailed Datastructures with Two Scale Factors for Deep Neural Networks. | Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang |
| 2019 | HiPC | Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems. | Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Philip Heidelberger, Leland Chang, Kailash Gopalakrishnan |
| 2019 | ICASSP | Workload-aware Automatic Parallelization for Multi-GPU DNN Training. | Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung |
| 2019 | ICLR | Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. | Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan |
| 2018 | AAAI | AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. | Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan |
| 2018 | DAC | Compensated-DNN: energy efficient low-precision deep neural networks by compensating quantization errors. | Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Pierce Chuang, Leland Chang |
| 2018 | DATE | Exploiting approximate computing for deep learning acceleration. | Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Viji Srinivasan, Swagath Venkataramani |
| 2018 | ICASSP | True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization. | Charbel Sakr, Jungwook Choi, Zhuo Wang, Kailash Gopalakrishnan, Naresh R. Shanbhag |
| 2018 | ISCA | PROMISE: An End-to-End Design of a Programmable Mixed-Signal Accelerator for Machine-Learning Algorithms. | Prakalp Srivastava, Mingu Kang, Sujan K. Gonugondla, Sungmin Lim, Jungwook Choi, Vikram S. Adve, Nam Sung Kim, Naresh R. Shanbhag |
| 2018 | ISLPED | 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, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan |
| 2018 | ISLPED | Taming the beast: Programming Peta-FLOP class Deep Learning Systems. | Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang |
| 2017 | DAC | Accelerator Design for Deep Learning Training: Extended Abstract: Invited. | Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Jinwook Oh, Sunil Shukla, Viji Srinivasan, Swagath Venkataramani, Wei Zhang |
| 2017 | FPL | Toward a pixel-parallel architecture for graph cuts inference on FPGA. | Tianqi Gao, Jungwook Choi, Shang-nien Tsai, Rob A. Rutenbar |
| 2016 | FPL | Configurable and scalable belief propagation accelerator for computer vision. | Jungwook Choi, Rob A. Rutenbar |
| 2016 | ICASSP | Analysis of error resiliency of belief propagation in computer vision. | Jungwook Choi, Ameya D. Patil, Rob A. Rutenbar, Naresh R. Shanbhag |
| 2015 | FPL | Fast hierarchical implementation of sequential tree-reweighted belief propagation for probabilistic inference. | Skand Hurkat, Jungwook Choi, Eriko Nurvitadhi, Jos F. Martnez, Rob A. Rutenbar |
| 2014 | ICASSP | A robust message passing based stereo matching kernel via system-level error resiliency. | Eric P. Kim, Jungwook Choi, Naresh R. Shanbhag, Rob A. Rutenbar |
| 2013 | FPGA | Video-rate stereo matching using markov random field TRW-S inference on a hybrid CPU+FPGA computing platform. | Jungwook Choi, Rob A. Rutenbar |
| 2013 | ISPASS | EMERALD: Characterization of emerging applications and algorithms for low-power devices. | Chuanjun Zhang, Glenn G. Ko, Jungwook Choi, Shang-nien Tsai, Minje Kim, Abner Guzmn-Rivera, Rob A. Rutenbar, Paris Smaragdis, Mi Sun Park, Vijaykrishnan Narayanan, Hongyi Xin, Onur Mutlu, Bin Li, Li Zhao, Mei Chen |
| 2013 | MEMOCODE | FPGA acceleration of Markov Random Field TRW-S inference for stereo matching. | Jungwook Choi, Rob A. Rutenbar |
| 2012 | FPL | Hardware implementation of MRF map inference on an FPGA platform. | Jungwook Choi, Rob A. Rutenbar |
| 2010 | ICASSP | An FPGA implementation of speech recognition with weighted finite state transducers. | Jungwook Choi, Kisun You, Wonyong Sung |
| 2010 | MOBICOM | Supporting handover in an IEEE 802.11p-based wireless access system. | Jungwook Choi, Hyukjoon Lee |
| 2009 | ICASSP | VLSI for 5000-word continuous speech recognition. | Young-kyu Choi, Kisun You, Jungwook Choi, Wonyong Sung |
| 2006 | IROS | A Study on the Development of Ubiquitous CellPhone Robot. | Seungwoo Kim, Dongik Oh, Dongwook Kim, Yongrae Jung, Jacil Choe, Jungwook Choi |