Sungjun Cho

According to our database, Sungjun Cho authored at least 26 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Partial-Multivariate Model for Forecasting.

Jaehoon Lee, Hankook Lee, Sungik Choi, Sungjun Cho, 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

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

Block-SSD: A New Block-Based Blocking SSD Architecture.

Ryan Wong, Arjun Tyagi, Sungjun Cho, Pratik Sampat, Yiqiu Sun

CoRR, 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

CR2: Community-aware Compressed Regular Representation for Graph Processing on a GPU.

Shinnung Jeong, Sungjun Cho, Yongwoo Lee, Hyunjun Park, Seonyeong Heo, Gwangsun Kim, Youngsok Kim, Hanjun Kim

Proceedings of the 53rd International Conference on Parallel Processing, 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

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers.

Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

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

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

CoRR, 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

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning.

Sungmin Cha, Sungjun Cho, Dasol Hwang, Sunwon Hong, Moontae Lee, Taesup Moon

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

PIMFlow: Compiler and Runtime Support for CNN Models on Processing-in-Memory DRAM.

Yongwon Shin, Juseong Park, Sungjun Cho, Hyojin Sung

Proceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization, 2023

Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters.

Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Pure Transformers are Powerful Graph Learners.

Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong

CoRR, 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, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Equivariant Hypergraph Neural Networks.

Jinwoo Kim, Saeyoon Oh, Sungjun Cho, Seunghoon Hong

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

On-the-fly Rectification for Robust Large-Vocabulary Topic Inference.

Moontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel

Proceedings of the 38th International Conference on Machine Learning, 2021

Thread-Aware Area-Efficient High-Level Synthesis Compiler for Embedded Devices.

Changsu Kim, Shinnung Jeong, Sungjun Cho, Yongwoo Lee, William Song, Youngsok Kim, Hanjun Kim

Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2021

2020

Real-Time Object Detection System with Multi-Path Neural Networks.

Seonyeong Heo, Sungjun Cho, Youngsok Kim, Hanjun Kim

Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, 2020

2019

Practical Correlated Topic Modeling and Analysis via the Rectified Anchor Word Algorithm.

Moontae Lee, Sungjun Cho, David Bindel, David Mimno

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019