PAMAE: Parallel k-Medoids Clustering with High Accuracy and Efficiency. - Hwanjun Song; Jae-Gil Lee 001; Wook-Shin Han (KDD, 2017)

RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning. - Hwanjun Song; Jae-Gil Lee 001 (SIGMOD Conference, 2018)

SELFIE: Refurbishing Unclean Samples for Robust Deep Learning. - Hwanjun Song; Minseok Kim; Jae-Gil Lee 001 (ICML, 2019)

MLAT: Metric Learning for kNN in Streaming Time Series. - Dongmin Park; Susik Yoon; Hwanjun Song; Jae-Gil Lee 001 (CoRR, 2019)

Prestopping: How Does Early Stopping Help Generalization against Label Noise? - Hwanjun Song; Minseok Kim; Dongmin Park; Jae-Gil Lee 001 (CoRR, 2019)

Carpe Diem, Seize the Samples Uncertain "at the Moment" for Adaptive Batch Selection. - Hwanjun Song; Minseok Kim; Sundong Kim; Jae-Gil Lee 001 (CIKM, 2020)

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; Jae-Gil Lee 001 (KDD, 2020)

Revisit Prediction by Deep Survival Analysis. - Sundong Kim; Hwanjun Song; Sejin Kim 002; Beomyoung Kim; Jae-Gil Lee 001 (PAKDD (2), 2020)

TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data. - Dongmin Park; Hwanjun Song; Minseok Kim; Jae-Gil Lee 001 (WWW, 2020)

Learning from Noisy Labels with Deep Neural Networks: A Survey. - Hwanjun Song; Minseok Kim; Dongmin Park; Jae-Gil Lee 001 (CoRR, 2020)

Two-Phase Learning for Overcoming Noisy Labels. - Hwanjun Song; Minseok Kim; Dongmin Park; Jae-Gil Lee 001 (CoRR, 2020)

Ada-boundary: accelerating DNN training via adaptive boundary batch selection. - Hwanjun Song; Sundong Kim; Minseok Kim; Jae-Gil Lee 001 (Mach. Learn., 2020)

PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation. - Minseok Kim; Hwanjun Song; Doyoung Kim; Kijung Shin; Jae-Gil Lee 001 (AAAI, 2021)

Exploiting Scene Depth for Object Detection with Multimodal Transformers. - Hwanjun Song; Eunyoung Kim; Varun Jampani; Deqing Sun; Jae-Gil Lee 001; Ming-Hsuan Yang 001 (BMVC, 2021)

Machine Learning Robustness, Fairness, and their Convergence. - Jae-Gil Lee 001; Yuji Roh; Hwanjun Song; Steven Euijong Whang (KDD, 2021)

Robust Learning by Self-Transition for Handling Noisy Labels. - Hwanjun Song; Minseok Kim; Dongmin Park; Yooju Shin; Jae-Gil Lee 001 (KDD, 2021)

Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data. - Dongmin Park; Hwanjun Song; Minseok Kim; Jae-Gil Lee 001 (NeurIPS, 2021)

COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies. - Doyoung Kim; Hyangsuk Min; Youngeun Nam; Hwanjun Song; Susik Yoon; Minseok Kim; Jae-Gil Lee 001 (AAAI, 2022)

Meta-Learning for Online Update of Recommender Systems. - Minseok Kim; Hwanjun Song; Yooju Shin; Dongmin Park; Kijung Shin; Jae-Gil Lee 001 (AAAI, 2022)

FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning. - Sangmook Kim; Wonyoung Shin; Soohyuk Jang; Hwanjun Song; Se-Young Yun (CIKM, 2022)

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (CIKM, 2022)

e-CLIP: Large-Scale Vision-Language Representation Learning in E-commerce. - Wonyoung Shin; Jonghun Park; Taekang Woo; Yongwoo Cho 003; Kwangjin Oh; Hwanjun Song (CIKM, 2022)

Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries. - Jihwan Bang; Hyunseo Koh; Seulki Park; Hwanjun Song; Jung-Woo Ha 001; Jonghyun Choi (CVPR, 2022)

Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases. - Dongmin Park; Junhyeok Kang; Hwanjun Song; Susik Yoon; Jae-Gil Lee 001 (ICDM, 2022)

Coherence-based Label Propagation over Time Series for Accelerated Active Learning. - Yooju Shin; Susik Yoon; Sundong Kim; Hwanjun Song; Jae-Gil Lee 001; Byung Suk Lee 001 (ICLR, 2022)

ViDT: An Efficient and Effective Fully Transformer-based Object Detector. - Hwanjun Song; Deqing Sun; Sanghyuk Chun; Varun Jampani; Dongyoon Han; Byeongho Heo; Wonjae Kim; Ming-Hsuan Yang 001 (ICLR, 2022)

Dataset Condensation via Efficient Synthetic-Data Parameterization. - Jang-Hyun Kim; Jinuk Kim; Seong Joon Oh; Sangdoo Yun; Hwanjun Song; Joonhyun Jeong; Jung-Woo Ha 001; Hyun Oh Song (ICML, 2022)

Time Is MattEr: Temporal Self-supervision for Video Transformers. - Sukmin Yun; Jaehyung Kim 001; Dongyoon Han; Hwanjun Song; Jung-Woo Ha 001; Jinwoo Shin (ICML, 2022)

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (NeurIPS, 2022)

Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning. - Dongmin Park; Yooju Shin; Jihwan Bang; Youngjun Lee; Hwanjun Song; Jae-Gil Lee 001 (NeurIPS, 2022)

Understanding Cross-Domain Few-Shot Learning: An Experimental Study. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (CoRR, 2022)

An Extendable, Efficient and Effective Transformer-based Object Detector. - Hwanjun Song; Deqing Sun; Sanghyuk Chun; Varun Jampani; Dongyoon Han; Byeongho Heo; Wonjae Kim; Ming-Hsuan Yang 001 (CoRR, 2022)

Re-Thinking Federated Active Learning Based on Inter-Class Diversity. - Sangmook Kim; Sangmin Bae; Hwanjun Song; Se-Young Yun (CVPR, 2023)

Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding. - Sangmin Bae; Jongwoo Ko; Hwanjun Song; Se-Young Yun (EMNLP, 2023)

Enhancing Abstractiveness of Summarization Models through Calibrated Distillation. - Hwanjun Song; Igor Shalyminov; Hang Su; Siffi Singh; Kaisheng Yao; Saab Mansour (EMNLP (Findings), 2023)

Generating Instance-level Prompts for Rehearsal-free Continual Learning. - Dahuin Jung; Dongyoon Han; Jihwan Bang; Hwanjun Song (ICCV, 2023)

Online Boundary-Free Continual Learning by Scheduled Data Prior. - Hyunseo Koh; Minhyuk Seo; Jihwan Bang; Hwanjun Song; Deokki Hong; Seulki Park; Jung-Woo Ha 001; Jonghyun Choi (ICLR, 2023)

Context Consistency Regularization for Label Sparsity in Time Series. - Yooju Shin; Susik Yoon; Hwanjun Song; Dongmin Park; Byunghyun Kim; Jae-Gil Lee 001; Byung Suk Lee 001 (ICML, 2023)

Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy. - Dongmin Park; Seola Choi; Doyoung Kim; Hwanjun Song; Jae-Gil Lee 001 (NeurIPS, 2023)

Q-HyViT: Post-Training Quantization for Hybrid Vision Transformer with Bridge Block Reconstruction. - Jemin Lee; Yongin Kwon; Jeman Park 002; Misun Yu; Hwanjun Song (CoRR, 2023)

Prompt-Guided Transformers for End-to-End Open-Vocabulary Object Detection. - Hwanjun Song; Jihwan Bang (CoRR, 2023)

Data collection and quality challenges in deep learning: a data-centric AI perspective. - Steven Euijong Whang; Yuji Roh; Hwanjun Song; Jae-Gil Lee 001 (VLDB J., 2023)

Learning From Noisy Labels With Deep Neural Networks: A Survey. - Hwanjun Song; Minseok Kim; Dongmin Park; Yooju Shin; Jae-Gil Lee 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Adaptive Shortcut Debiasing for Online Continual Learning. - Doyoung Kim; Dongmin Park; Yooju Shin; Jihwan Bang; Hwanjun Song; Jae-Gil Lee 001 (AAAI, 2024)

Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise. - Hwanjun Song; Minseok Kim; Jae-Gil Lee 001 (AAAI, 2024)

FineSurE: Fine-grained Summarization Evaluation using LLMs. - Hwanjun Song; Hang Su; Igor Shalyminov; Jason Cai; Saab Mansour (ACL (1), 2024)

Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders. - Yuwei Zhang; Siffi Singh; Sailik Sengupta; Igor Shalyminov; Hang Su; Hwanjun Song; Saab Mansour (ACL (1), 2024)

Controllable Contextualized Image Captioning: Directing the Visual Narrative Through User-Defined Highlights. - Shunqi Mao; Chaoyi Zhang; Hang Su; Hwanjun Song; Igor Shalyminov; Weidong Cai 001 (ECCV (50), 2024)

UniSumEval: Towards Unified, Fine-grained, Multi-dimensional Summarization Evaluation for LLMs. - Yuho Lee; Taewon Yun; Jason Cai; Hang Su; Hwanjun Song (EMNLP (Findings), 2024)

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; Jae-Gil Lee 001 (ICML, 2024)

MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets. - Hossein Aboutalebi; Hwanjun Song; Yusheng Xie; Arshit Gupta; Lijia Sun; Hang Su; Igor Shalyminov; Nikolaos Pappas 004; Siffi Singh; Saab Mansour (NAACL-HLT, 2024)

Semi-Supervised Dialogue Abstractive Summarization via High-Quality Pseudolabel Selection. - Jianfeng He; Hang Su; Jason Cai; Igor Shalyminov; Hwanjun Song; Saab Mansour (NAACL-HLT, 2024)

TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization. - Liyan Tang; Igor Shalyminov; Amy Wing-mei Wong; Jon Burnsky; Jake W. Vincent; Yuan Yang; Siffi Singh; Song Feng 001; Hwanjun Song; Hang Su; Lijia Sun; Yi Zhang 053; et al. (NAACL-HLT, 2024)

Exploiting Representation Curvature for Boundary Detection in Time Series. - Yooju Shin; Jaehyun Park; Susik Yoon; Hwanjun Song; Byung Suk Lee 001; Jae-Gil Lee 001 (NeurIPS, 2024)

Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection. - Youngeun Nam; Susik Yoon; Yooju Shin; Minyoung Bae; Hwanjun Song; Jae-Gil Lee 001; Byung Suk Lee 001 (WWW, 2024)

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 004; Siffi Singh; Saab Mansour (CoRR, 2024)

Learning to Summarize from LLM-generated Feedback. - Hwanjun Song; Taewon Yun; Yuho Lee; Gihun Lee; Jason Cai; Hang Su (CoRR, 2024)

In-Context Learning with Noisy Labels. - Junyong Kang; Donghyun Son; Hwanjun Song; Buru Chang (CoRR, 2024)

Prompt-guided DETR with RoI-pruned masked attention for open-vocabulary object detection. - Hwanjun Song; Jihwan Bang (Pattern Recognit., 2024)

Q-HyViT: Post-Training Quantization of Hybrid Vision Transformers With Bridge Block Reconstruction for IoT Systems. - Jemin Lee; Yongin Kwon; Sihyeong Park; Misun Yu; Jeman Park 002; Hwanjun Song (IEEE Internet Things J., 2024)

Word2Passage: Word-level Importance Re-weighting for Query Expansion. - Jeonghwan Choi; Minjeong Ban; Minseok Kim; Hwanjun Song (ACL (Findings), 2025)

Towards Multi-dimensional Evaluation of LLM Summarization across Domains and Languages. - Hyangsuk Min; Yuho Lee; Minjeong Ban; Jiaqi Deng; Nicole Hee-Yeon Kim; Taewon Yun; Hang Su; Jason Cai; Hwanjun Song (ACL (1), 2025)

Learning to Verify Summary Facts with Fine-Grained LLM Feedback. - Jihwan Oh; Jeonghwan Choi; Nicole Hee-Yeon Kim; Taewon Yun; Hwanjun Song (COLING, 2025)

RA-TTA: Retrieval-Augmented Test-Time Adaptation for Vision-Language Models. - Youngjun Lee; Doyoung Kim; Junhyeok Kang; Jihwan Bang; Hwanjun Song; Jae-Gil Lee 001 (ICLR, 2025)

Mobility Networked Time-Series Forecasting Benchmark Datasets. - Jihye Na; Youngeun Nam; Susik Yoon; Hwanjun Song; Byung Suk Lee 001; Jae-Gil Lee 001 (ICWSM, 2025)

Faithful, Unfaithful or Ambiguous? Multi-Agent Debate with Initial Stance for Summary Evaluation. - Mahnaz Koupaee; Jake W. Vincent; Saab Mansour; Igor Shalyminov; Han He; Hwanjun Song; Raphael Shu; Jianfeng He; Yi Nian; Amy Wing-mei Wong; Kyu J. Han; Hang Su (NAACL (Long Papers), 2025)

Learning to Summarize from LLM-generated Feedback. - Hwanjun Song; Taewon Yun; Yuho Lee; Jihwan Oh; Gihun Lee; Jason Cai; Hang Su (NAACL (Long Papers), 2025)

LLM-based User Profile Management for Recommender System. - Seunghwan Bang; Hwanjun Song (CoRR, 2025)

Ext2Gen: Alignment through Unified Extraction and Generation for Robust Retrieval-Augmented Generation. - Hwanjun Song; Jeonghwan Choi; Minseok Kim (CoRR, 2025)

ReFeed: Multi-dimensional Summarization Refinement with Reflective Reasoning on Feedback. - Taewon Yun; Jihwan Oh; Hyangsuk Min; Yuho Lee; Jihwan Bang; Jason Cai; Hwanjun Song (CoRR, 2025)

Rethinking LLM-Based Recommendations: A Query Generation-Based, Training-Free Approach. - Donghee Han; Hwanjun Song; Mun Yong Yi (CoRR, 2025)

References Indeed Matter? Reference-Free Preference Optimization for Conversational Query Reformulation. - Doyoung Kim; Youngjun Lee; Joeun Kim; Jihwan Bang; Hwanjun Song; Susik Yoon; Jae-Gil Lee 001 (CoRR, 2025)