Publications

We publish our research in high-impact conferences and journals within the field of Computer Science. We have collaborated top IT tech companies such as AWS AI Labs, Google Research, and NAVER AI Lab.
As of now, we published more than 30 CS top confernces in various domains, including NLP (EMNLP), CV (ICCV, CVPR), ML (NeurIPS, ICLR, ICML, AAAI), DM (KDD, CIKM, ICDM, WWW, SIGMOD).

Asterisk (*) denotes corresponding authors.

International Conferences and Journals

2024

  1. MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets
    Hossein Aboutalebi, Hwanjun Song*, Yusheng Xie, Arshit Gupta, Justin Sun, Hang Su, Igor Shalyminov, Nikolaos Pappas, Siffi Singh, and Saab Mansour
    In Annual Conference of the North American Chapter of the Association for Computational Linguistics (Top Conference, Oral), 2024
  2. TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
    Liyan Tang, Igor Shalyminov, Amy Wing-mei Wong, Jon Burnsky, Jake W Vincent, Yu’an Yang, Siffi Singh, Song Feng, Hwanjun Song, Hang Su, and 1 more author
    In Annual Conference of the North American Chapter of the Association for Computational Linguistics (Top Conference, Poster), 2024
  3. Semi-Supervised Dialogue Abstractive Summarization via High-Quality Pseudolabel Selection
    Jianfeng He, Hang Su, Jason Cai, Igor Shalyminov, Hwanjun Song, and Saab Mansour
    In Annual Conference of the North American Chapter of the Association for Computational Linguistics (Top Conference, Oral), 2024
  4. arXiv
    Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders
    Yuwei Zhang, Siffi Singh, Sailik Sengupta, Igore Shalyminov, Hang Su, Hwanjun Song, and Saab Mansour
    arXiv preprint arXiv:2403.04314, 2024
  5. Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection
    Youngeun Nam, Susik Yoon, Yooju Shin, Minyoung Bae, Hwanjun Song, Jae-Gil Lee*, and Byung Suk Lee
    In Proceedings of The Web Conference (Top Conference), 2024
  6. Adaptive Shortcut Debiasing for Online Continual Learning
    Doyoung Kim, Dongmin Park, Yooju Shin, Jihwan Bang, Hwanjun Song, and Jae-Gil Lee*
    In AAAI Conference on Artificial Intelligence (Top Conference), 2024
  7. Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise
    Hwanjun Song*, Minseok Kim, and Jae-Gil Lee
    In AAAI Conference on Artificial Intelligence (Top Conference), 2024

2023

  1. arXiv
    One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning
    Doyoung Kim, Susik Yoon, Dongmin Park, Youngjun Lee, Hwanjun Song, Jihwan Bang, and Jae-Gil Lee*
    arXiv preprint arXiv:2311.12048, 2023
  2. Enhancing Abstractiveness of Summarization Models through Calibrated Distillation
    Hwanjun Song*, Igor Shalyminov, Hang Su, Siffi Singh, Kaisheng Yao, and Saab Mansour
    In International Conference on Empirical Methods in Natural Language Processing (Top Conference), 2023
  3. Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding
    Sangmin Bae, Jongwoo Ko, Hwanjun Song*, and Se-Young Yun*
    In International Conference on Empirical Methods in Natural Language Processing (Top Conference), 2023
  4. Robust data pruning under label noise via maximizing re-labeling accuracy
    Dongmin Park, Seola Choi, Doyoung Kim, Hwanjun Song, and Jae-Gil Lee*
    In Advances in Neural Information Processing Systems (Top Conference), 2023
  5. Prompt-Guided Detr with Roi-Pruned Masked Attention for Open-Vocabulary Object Detection
    Hwanjun Song*, and Jihwan Bang
    SSRN 4623541, 2023
  6. ICCV Oral
    Generating instance-level prompts for rehearsal-free continual learning
    Dahuin Jung, Dongyoon Han, Jihwan Bang, and Hwanjun Song*
    In International Conference on Computer Vision (Top Conference), 2023
  7. Context Consistency Regularization for Label Sparsity in Time Series
    Yooju Shin, Susik Yoon, Hwanjun Song, Dongmin Park, Byunghyun Kim, Jae-Gil Lee*, and Byung Suk Lee
    In International Conference on Machine Learning (Top Conference), 2023
  8. arXiv
    Q-HyViT: Post-Training Quantization for Hybrid Vision Transformer with Bridge Block Reconstruction
    Jemin Lee, Yongin Kwon, Jeman Park, Misun Yu, and Hwanjun Song*
    arXiv preprint arXiv:2303.12557, 2023
  9. Re-thinking Federated Active Learning based on Inter-class Diversity
    SangMook Kim, Sangmin Bae, Hwanjun Song*, and Se-Young Yun*
    In International Conference on Computer Vision and Pattern Recognition (Top Conference), 2023
  10. Online Boundary-Free Continual Learning by Scheduled Data Prior
    Hyunseo Koh, Minhyuk Seo, Jihwan Bang, Hwanjun Song, Deokki Hong, Seulki Park, Jung-Woo Ha, and Jonghyun Choi*
    In International Conference on Learning Representations (Top Conference), 2023
  11. Data collection and quality challenges in deep learning: A data-centric ai perspective
    Steven Euijong Whang, Yuji Roh, Hwanjun Song, and Jae-Gil Lee*
    The VLDB Journal, 2023

2022

  1. Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning
    Dongmin Park, Yooju Shin, Jihwan Bang, Youngjun Lee, Hwanjun Song*, and Jae-Gil Lee*
    In Advances in Neural Information Processing Systems (Top Conference), 2022
  2. Understanding cross-domain few-shot learning: An experimental study
    Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Song*, and Se-Young Yun*
    In Advances in Neural Information Processing Systems (Top Conference), 2022
  3. Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases
    Dongmin Park, Junhyeok Kang, Hwanjun Song, Susik Yoon, and Jae-Gil Lee*
    In International Conference on Data Mining (Top Conference), 2022
  4. E-CLIP: Large-scale vision-language representation learning in e-commerce
    Wonyoung Shin, Jonghun Park, Taekang Woo, Yongwoo Cho, Kwangjin Oh, and Hwanjun Song*
    In International Conference on Information and Knowledge Management (Top Conference), 2022
  5. ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning
    Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Song*, and Se-Young Yun*
    In International Conference on Information and Knowledge Management (Top Conference), 2022
  6. FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning
    Sangmook Kim, Wonyoung Shin, Soohyuk Jang, Hwanjun Song*, and Se-Young Yun*
    In International Conference on Information and Knowledge Management (Top Conference), 2022
  7. Learning from noisy labels with deep neural networks: A survey
    Hwanjun Song, Minseok Kim, Dongmin Park, Yooju Shin, and Jae-Gil Lee*
    IEEE Transactions on Neural Networks and Learning Systems, 2022
  8. Time Is MattEr: Temporal Self-supervision for Video Transformers
    Sukmin Yun, Jaehyung Kim, Dongyoon Han, Hwanjun Song, Jung-Woo Ha, and Jinwoo Shin*
    In International Conference on Machine Learning (Top Conference), 2022
  9. Dataset condensation via efficient synthetic-data parameterization
    Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh, Sangdoo Yun, Hwanjun Song, Joonhyun Jeong, Jung-Woo Ha, and Hyun Oh Song*
    In International Conference on Machine Learning (Top Conference), 2022
  10. Coherence-based label propagation over time series for accelerated active learning
    Yooju Shin, Susik Yoon, Sundong Kim, Hwanjun Song, Jae-Gil Lee*, and Byung Suk Lee
    In International Conference on Learning Representations (Top Conference), 2022
  11. VIDT: An efficient and effective fully transformer-based object detector
    Hwanjun Song*, Deqing Sun, Sanghyuk Chun, Varun Jampani, Dongyoon Han, Byeongho Heo, Wonjae Kim, and Ming-Hsuan Yang
    In International Conference on Learning Representations (Top Conference), 2022
  12. Meta-learning for online update of recommender systems
    Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, and Jae-Gil Lee*
    In AAAI Conference on Artificial Intelligence (Top Conference), 2022
  13. AAAI Oral
    Covid-EENet: Predicting fine-grained impact of COVID-19 on local economies
    Doyoung Kim, Hyangsuk Min, Youngeun Nam, Hwanjun Song, Susik Yoon, Minseok Kim, and Jae-Gil Lee*
    In AAAI Conference on Artificial Intelligence (Top Conference), 2022
  14. Online continual learning on a contaminated data stream with blurry task boundaries
    Jihwan Bang, Hyunseo Koh, Seulki Park, Hwanjun Song, Jung-Woo Ha, and Jonghyun Choi*
    In International Conference on Computer Vision and Pattern Recognition (Top Conference), 2022

2021

  1. Task-agnostic undesirable feature deactivation using out-of-distribution data
    Dongmin Park, Hwanjun Song, MinSeok Kim, and Jae-Gil Lee*
    In Advances in Neural Information Processing Systems (Top Conference), 2021
  2. Exploiting scene depth for object detection with multimodal transformers
    Hwanjun Song*, Eunyoung Kim, Varun Jampan, Deqing Sun, Jae-Gil Lee, and Ming-Hsuan Yang
    In British Machine Vision Conference, 2021
  3. KDD Oral
    Robust learning by self-transition for handling noisy labels
    Hwanjun Song, Minseok Kim, Dongmin Park, Yooju Shin, and Jae-Gil Lee*
    In International Conference on Knowledge Discovery and Data Mining (Top Conference), 2021
  4. Machine learning robustness, fairness, and their convergence
    Jae-Gil Lee, Yuji Roh, Hwanjun Song, and Steven Euijong Whang*
    In International Conference on Knowledge Discovery and Data Mining (Top Conference), 2021
  5. Premere: Meta-reweighting via self-ensembling for point-of-interest recommendation
    Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, and Jae-Gil Lee*
    In AAAI Conference on Artificial Intelligence (Top Conference), 2021

2020

  1. CIKM Oral
    Carpe Diem, Seize the Samples Uncertain" at the Moment" for Adaptive Batch Selection
    Hwanjun Song, Minseok Kim, Sundong Kim, and Jae-Gil Lee*
    In International Conference on Information and Knowledge Management (Top Conference), 2020
  2. Ada-boundary: accelerating DNN training via adaptive boundary batch selection
    Hwanjun Song, Sundong Kim, Minseok Kim, and Jae-Gil Lee*
    Machine Learning, 2020
  3. KDD Oral
    Hi-COVIDNet: Deep learning approach to predict inbound COVID-19 patients and case study in South Korea
    Minseok Kim, Junhyeok Kang, Doyoung Kim, Hwanjun Song, Hyangsuk Min, Youngeun Nam, Dongmin Park, and Jae-Gil Lee*
    In International Conference on Knowledge Discovery and Data Mining (Top Conference), 2020
  4. Revisit Prediction by Deep Survival Analysis
    Sundong Kim, Hwanjun Song, Sejin Kim, Beomyoung Kim, and Jae-Gil Lee*
    In Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2020
  5. WWW Oral
    TRAP: Two-level regularized autoencoder-based embedding for power-law distributed data
    Dongmin Park, Hwanjun Song, Minseok Kim, and Jae-Gil Lee*
    In Proceedings of The Web Conference (Top Conference), 2020

2019

  1. ICML Spotlight
    SELFIE: Refurbishing unclean samples for robust deep learning
    Hwanjun Song, Minseok Kim, and Jae-Gil Lee*
    In International Conference on Machine Learning (Top Conference), 2019

2018

  1. SIGMOD Oral
    RP-DBSCAN: A superfast parallel DBSCAN algorithm based on random partitioning
    Hwanjun Song, and Jae-Gil Lee*
    In International Conference on Management of Data (Top Conference), 2018

2017

  1. PAMAE: parallel k-medoids clustering with high accuracy and efficiency
    Hwanjun Song, Jae-Gil Lee*, and Wook-Shin Han
    In International Conference on Knowledge Discovery and Data Mining (Top Conference), 2017