| 2026 | ACL | Distilling LLM Reasoning into Dense Encoders: Bridging the Accuracy-Efficiency Gap in Recommendation. | Donghee Han, Daeyoung Roh, A Young Kim, Hwanjun Song, Mun Yong Yi |
| 2026 | ACL | QuDAR: Query-Wise Dual-Perspective Adaptive Retrieval. | Joeun Kim, Seunghyouk Yoon, Xuan-Bach Le, Youngeun Nam, Doyoung Kim, Hwanjun Song, Jae-Gil Lee |
| 2026 | ACL | Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data Pipelines. | Hwanjun Song |
| 2026 | ACL | Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding. | Taewon Yun, Jisu Shin, Jeonghwan Choi, Seunghwan Bang, Hwanjun Song |
| 2026 | WSDM | Aligning Extraction and Generation for Robust Retrieval-Augmented Generation. | Hwanjun Song, Jeonghwan Choi, Minseok Kim |
| 2025 | ACL | Word2Passage: Word-level Importance Re-weighting for Query Expansion. | Jeonghwan Choi, Minjeong Ban, Minseok Kim, Hwanjun Song |
| 2025 | ACL | 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 |
| 2025 | COLING | Learning to Verify Summary Facts with Fine-Grained LLM Feedback. | Jihwan Oh, Jeonghwan Choi, Nicole Hee-Yeon Kim, Taewon Yun, Hwanjun Song |
| 2025 | EMNLP | Rethinking LLM-Based Recommendations: A Personalized Query-Driven Parallel Integration. | Donghee Han, Hwanjun Song, Mun Yong Yi |
| 2025 | EMNLP | Towards a Holistic and Automated Evaluation Framework for Multi-Level Comprehension of LLMs in Book-Length Contexts. | Yuho Lee, Jiaqi Deng, Nicole Hee-Yeon Kim, Hyangsuk Min, Taewon Yun, Minjeong Ban, Kim Yul, Hwanjun Song |
| 2025 | ICCV | Robust Dataset Condensation using Supervised Contrastive Learning. | Nicole Hee-Yeon Kim, Hwanjun Song |
| 2025 | ICLR | RA-TTA: Retrieval-Augmented Test-Time Adaptation for Vision-Language Models. | Youngjun Lee, Doyoung Kim, Junhyeok Kang, Jihwan Bang, Hwanjun Song, Jae-Gil Lee |
| 2025 | ICWSM | Mobility Networked Time-Series Forecasting Benchmark Datasets. | Jihye Na, Youngeun Nam, Susik Yoon, Hwanjun Song, Byung Suk Lee, Jae-Gil Lee |
| 2025 | KDD | Bi-Modal Learning for Networked Time Series. | Youngeun Nam, Jihye Na, Susik Yoon, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee |
| 2025 | NAACL | 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 |
| 2025 | NAACL | Learning to Summarize from LLM-generated Feedback. | Hwanjun Song, Taewon Yun, Yuho Lee, Jihwan Oh, Gihun Lee, Jason Cai, Hang Su |
| 2024 | AAAI | Adaptive Shortcut Debiasing for Online Continual Learning. | Doyoung Kim, Dongmin Park, Yooju Shin, Jihwan Bang, Hwanjun Song, Jae-Gil Lee |
| 2024 | AAAI | Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise. | Hwanjun Song, Minseok Kim, Jae-Gil Lee |
| 2024 | ACL | FineSurE: Fine-grained Summarization Evaluation using LLMs. | Hwanjun Song, Hang Su, Igor Shalyminov, Jason Cai, Saab Mansour |
| 2024 | ACL | 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 |
| 2024 | ECCV | Controllable Contextualized Image Captioning: Directing the Visual Narrative Through User-Defined Highlights. | Shunqi Mao, Chaoyi Zhang, Hang Su, Hwanjun Song, Igor Shalyminov, Weidong Cai |
| 2024 | EMNLP | UniSumEval: Towards Unified, Fine-grained, Multi-dimensional Summarization Evaluation for LLMs. | Yuho Lee, Taewon Yun, Jason Cai, Hang Su, Hwanjun Song |
| 2024 | ICML | 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 |
| 2024 | NAACL | 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, Siffi Singh, Saab Mansour |
| 2024 | NAACL | Semi-Supervised Dialogue Abstractive Summarization via High-Quality Pseudolabel Selection. | Jianfeng He, Hang Su, Jason Cai, Igor Shalyminov, Hwanjun Song, Saab Mansour |
| 2024 | NAACL | 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, Hwanjun Song, Hang Su, Lijia Sun, Yi Zhang, Saab Mansour, Kathleen McKeown |
| 2024 | WWW | Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection. | Youngeun Nam, Susik Yoon, Yooju Shin, Minyoung Bae, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee |
| 2023 | CVPR | Re-Thinking Federated Active Learning Based on Inter-Class Diversity. | Sangmook Kim, Sangmin Bae, Hwanjun Song, Se-Young Yun |
| 2023 | EMNLP | Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding. | Sangmin Bae, Jongwoo Ko, Hwanjun Song, Se-Young Yun |
| 2023 | EMNLP | Enhancing Abstractiveness of Summarization Models through Calibrated Distillation. | Hwanjun Song, Igor Shalyminov, Hang Su, Siffi Singh, Kaisheng Yao, Saab Mansour |
| 2023 | ICCV | Generating Instance-level Prompts for Rehearsal-free Continual Learning. | Dahuin Jung, Dongyoon Han, Jihwan Bang, Hwanjun Song |
| 2023 | ICLR | Online Boundary-Free Continual Learning by Scheduled Data Prior. | Hyunseo Koh, Minhyuk Seo, Jihwan Bang, Hwanjun Song, Deokki Hong, Seulki Park, Jung-Woo Ha, Jonghyun Choi |
| 2023 | ICML | Context Consistency Regularization for Label Sparsity in Time Series. | Yooju Shin, Susik Yoon, Hwanjun Song, Dongmin Park, Byunghyun Kim, Jae-Gil Lee, Byung Suk Lee |
| 2022 | AAAI | 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 |
| 2022 | AAAI | Meta-Learning for Online Update of Recommender Systems. | Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee |
| 2022 | CIKM | FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning. | Sangmook Kim, Wonyoung Shin, Soohyuk Jang, Hwanjun Song, Se-Young Yun |
| 2022 | CIKM | 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 |
| 2022 | CIKM | e-CLIP: Large-Scale Vision-Language Representation Learning in E-commerce. | Wonyoung Shin, Jonghun Park, Taekang Woo, Yongwoo Cho, Kwangjin Oh, Hwanjun Song |
| 2022 | CVPR | Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries. | Jihwan Bang, Hyunseo Koh, Seulki Park, Hwanjun Song, Jung-Woo Ha, Jonghyun Choi |
| 2022 | ICDM | 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 |
| 2022 | ICLR | Coherence-based Label Propagation over Time Series for Accelerated Active Learning. | Yooju Shin, Susik Yoon, Sundong Kim, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee |
| 2022 | ICLR | 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 |
| 2022 | ICML | Dataset Condensation via Efficient Synthetic-Data Parameterization. | Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh, Sangdoo Yun, Hwanjun Song, Joonhyun Jeong, Jung-Woo Ha, Hyun Oh Song |
| 2022 | ICML | Time Is MattEr: Temporal Self-supervision for Video Transformers. | Sukmin Yun, Jaehyung Kim, Dongyoon Han, Hwanjun Song, Jung-Woo Ha, Jinwoo Shin |
| 2021 | AAAI | PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation. | Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, Jae-Gil Lee |
| 2021 | BMVC | Exploiting Scene Depth for Object Detection with Multimodal Transformers. | Hwanjun Song, Eunyoung Kim, Varun Jampani, Deqing Sun, Jae-Gil Lee, Ming-Hsuan Yang |
| 2021 | KDD | Machine Learning Robustness, Fairness, and their Convergence. | Jae-Gil Lee, Yuji Roh, Hwanjun Song, Steven Euijong Whang |
| 2021 | KDD | Robust Learning by Self-Transition for Handling Noisy Labels. | Hwanjun Song, Minseok Kim, Dongmin Park, Yooju Shin, Jae-Gil Lee |
| 2020 | CIKM | Carpe Diem, Seize the Samples Uncertain "at the Moment" for Adaptive Batch Selection. | Hwanjun Song, Minseok Kim, Sundong Kim, Jae-Gil Lee |
| 2020 | KDD | 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 |
| 2020 | PAKDD | Revisit Prediction by Deep Survival Analysis. | Sundong Kim, Hwanjun Song, Sejin Kim, Beomyoung Kim, Jae-Gil Lee |
| 2020 | WWW | TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data. | Dongmin Park, Hwanjun Song, Minseok Kim, Jae-Gil Lee |
| 2019 | ICML | SELFIE: Refurbishing Unclean Samples for Robust Deep Learning. | Hwanjun Song, Minseok Kim, Jae-Gil Lee |
| 2018 | SIGMOD | RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning. | Hwanjun Song, Jae-Gil Lee |
| 2017 | KDD | PAMAE: Parallel | Hwanjun Song, Jae-Gil Lee, Wook-Shin Han |