Practical Correlated Topic Modeling and Analysis via the Rectified Anchor Word Algorithm. - Moontae Lee; Sungjun Cho; David Bindel; David Mimno (EMNLP/IJCNLP (1), 2019)

Real-Time Object Detection System with Multi-Path Neural Networks. - Seonyeong Heo; Sungjun Cho; Youngsok Kim; Hanjun Kim 001 (RTAS, 2020)

Thread-Aware Area-Efficient High-Level Synthesis Compiler for Embedded Devices. - Changsu Kim 004; Shinnung Jeong; Sungjun Cho; Yongwoo Lee 001; William Song; Youngsok Kim; Hanjun Kim 001 (CGO, 2021)

On-the-fly Rectification for Robust Large-Vocabulary Topic Inference. - Moontae Lee; Sungjun Cho; Kun Dong; David Mimno; David Bindel (ICML, 2021)

Equivariant Hypergraph Neural Networks. - Jinwoo Kim; Saeyoon Oh; Sungjun Cho; Seunghoon Hong (ECCV (21), 2022)

Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. - Sungjun Cho; Seonwoo Min; Jinwoo Kim; Moontae Lee; Honglak Lee; Seunghoon Hong (NeurIPS, 2022)

Pure Transformers are Powerful Graph Learners. - Jinwoo Kim; Dat Nguyen; Seonwoo Min; Sungjun Cho; Moontae Lee; Honglak Lee; Seunghoon Hong (NeurIPS, 2022)

Overcoming Memory Capacity Wall of GPUs With Heterogeneous Memory Stack. - Jeongmin Hong; Sungjun Cho; Gwangsun Kim (IEEE Comput. Archit. Lett., 2022)

Pure Transformers are Powerful Graph Learners. - Jinwoo Kim; Tien Dat Nguyen; Seonwoo Min; Sungjun Cho; Moontae Lee; Honglak Lee; Seunghoon Hong (CoRR, 2022)

Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters. - Sung Moon Ko; Sungjun Cho; Dae-Woong Jeong; Sehui Han; Moontae Lee; Honglak Lee (AAAI, 2023)

PIMFlow: Compiler and Runtime Support for CNN Models on Processing-in-Memory DRAM. - Yongwon Shin; Juseong Park; Sungjun Cho; Hyojin Sung (CGO, 2023)

Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning. - Sungmin Cha; Sungjun Cho; Dasol Hwang; Sunwon Hong; Moontae Lee; Taesup Moon (CVPR, 2023)

Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning. - HyunJae Lee; Gihyeon Lee; Junhwan Kim; Sungjun Cho; Dohyun Kim; Donggeun Yoo (WACV, 2023)

Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning. - Sungjun Cho; Seunghyuk Cho; Sungwoo Park; Hankook Lee; Honglak Lee; Moontae Lee (CoRR, 2023)

Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. - Sungmin Cha; Sungjun Cho; Dasol Hwang; Honglak Lee; Taesup Moon; Moontae Lee (AAAI, 2024)

AERO: Adaptive Erase Operation for Improving Lifetime and Performance of Modern NAND Flash-Based SSDs. - Sungjun Cho; Beomjun Kim; Hyunuk Cho; Gyeongseob Seo; Onur Mutlu; Myungsuk Kim; Jisung Park 001 (ASPLOS (3), 2024)

Show, Think, and Tell: Thought-Augmented Fine-Tuning of Large Language Models for Video Captioning. - Byoungjip Kim; Dasol Hwang; Sungjun Cho; Youngsoo Jang; Honglak Lee; Moontae Lee (CVPR Workshops, 2024)

Learning Equi-Angular Representations for Online Continual Learning. - Minhyuk Seo; Hyunseo Koh; Wonje Jeung; Minjae Lee; San Kim; Hankook Lee; Sungjun Cho; Sungik Choi; Hyunwoo Kim; Jonghyun Choi (CVPR, 2024)

Bandwidth-Effective DRAM Cache for GPU s with Storage-Class Memory. - Jeongmin Hong; Sungjun Cho; Geonwoo Park; Wonhyuk Yang; Young-Ho Gong; Gwangsun Kim (HPCA, 2024)

NORNS: Three Guides for Efficient Automatic Post-Fabrication Optimization of Modern NAND Flash Memory. - Earl Kim; Hyunuk Cho; Sungjun Cho; Myungsuk Kim; Jisung Park 001; Jaeyong Jeong; Eunkyoung Kim; Sunghoi Hur (ICCAD, 2024)

CR2: Community-aware Compressed Regular Representation for Graph Processing on a GPU. - Shinnung Jeong; Sungjun Cho; Yongwoo Lee 001; Hyunjun Park; Seonyeong Heo; Gwangsun Kim; Youngsok Kim; Hanjun Kim 001 (ICPP, 2024)

Bandwidth-Effective DRAM Cache for GPUs with Storage-Class Memory. - Jeongmin Hong; Sungjun Cho; Geonwoo Park; Wonhyuk Yang; Young-Ho Gong; Gwangsun Kim (CoRR, 2024)

Block-SSD: A New Block-Based Blocking SSD Architecture. - Ryan Wong; Arjun Tyagi; Sungjun Cho; Pratik Sampat; Yiqiu Sun 002 (CoRR, 2024)

Practical and Reproducible Symbolic Music Generation by Large Language Models with Structural Embeddings. - Seungyeon Rhyu; Kichang Yang; Sungjun Cho; Jaehyeon Kim; Kyogu Lee; Moontae Lee (CoRR, 2024)

Towards Robust and Cost-Efficient Knowledge Unlearning for Large Language Models. - Sungmin Cha; Sungjun Cho; Dasol Hwang; Moontae Lee (CoRR, 2024)

Partial-Multivariate Model for Forecasting. - Jaehoon Lee; Hankook Lee; Sungik Choi; Sungjun Cho; Moontae Lee (CoRR, 2024)

3D Denoisers Are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation. - Sungjun Cho; Dae-Woong Jeong; Sung Moon Ko; Jinwoo Kim; Sehui Han; Seunghoon Hong; Honglak Lee; Moontae Lee (AAAI, 2025)

Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs. - Sungmin Cha; Sungjun Cho; Dasol Hwang; Moontae Lee (ICLR, 2025)

TARDIS: Mitigating Temporal Misalignment via Representation Steering. - Changho Shin; Xinya Yan; Suenggwan Jo; Sungjun Cho; Shourjo Aditya Chaudhuri; Frederic Sala (CoRR, 2025)