Just-in-time WLANs: On-demand interference-managed WLAN infrastructures. - Kimin Lee; Yeonkeun Kim; Seokhyun Kim; Jinwoo Shin; Seungwon Shin; Song Chong (INFOCOM, 2016)

TravelMiner: On the Benefit of Path-Based Mobility Prediction. - Jaeseong Jeong; Kyunghan Lee; Beknazar Abdikamalov; Kimin Lee; Song Chong (SECON, 2016)

Confident Multiple Choice Learning. - Kimin Lee; Changho Hwang; KyoungSoo Park; Jinwoo Shin (ICML, 2017)

Simplified Stochastic Feedforward Neural Networks. - Kimin Lee; Jaehyung Kim 001; Song Chong; Jinwoo Shin (CoRR, 2017)

Hierarchical Novelty Detection for Visual Object Recognition. - Kibok Lee 003; Kimin Lee; Kyle Min 001; Yuting Zhang 001; Jinwoo Shin; Honglak Lee (CVPR, 2018)

Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples. - Kimin Lee; Honglak Lee; Kibok Lee 003; Jinwoo Shin (ICLR (Poster), 2018)

A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. - Kimin Lee; Kibok Lee 003; Honglak Lee; Jinwoo Shin (NeurIPS, 2018)

Learning to Specialize with Knowledge Distillation for Visual Question Answering. - Jonghwan Mun; Kimin Lee; Jinwoo Shin; Bohyung Han (NeurIPS, 2018)

Incremental Learning with Unlabeled Data in the Wild. - Kibok Lee 003; Kimin Lee; Jinwoo Shin; Honglak Lee (CVPR Workshops, 2019)

Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild. - Kibok Lee 003; Kimin Lee; Jinwoo Shin; Honglak Lee (ICCV, 2019)

Using Pre-Training Can Improve Model Robustness and Uncertainty. - Dan Hendrycks; Kimin Lee; Mantas Mazeika (ICML, 2019)

Robust Inference via Generative Classifiers for Handling Noisy Labels. - Kimin Lee; Sukmin Yun; Kibok Lee 003; Honglak Lee; Bo Li 026; Jinwoo Shin (ICML, 2019)

A Simple Randomization Technique for Generalization in Deep Reinforcement Learning. - Kimin Lee; Kibok Lee 003; Jinwoo Shin; Honglak Lee (CoRR, 2019)

Regularizing Class-Wise Predictions via Self-Knowledge Distillation. - Sukmin Yun; Jongjin Park; Kimin Lee; Jinwoo Shin (CVPR, 2020)

Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning. - Kimin Lee; Kibok Lee 003; Jinwoo Shin; Honglak Lee (ICLR, 2020)

Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning. - Kimin Lee; Younggyo Seo; Seunghyun Lee; Honglak Lee; Jinwoo Shin (ICML, 2020)

Reinforcement Learning with Augmented Data. - Michael Laskin; Kimin Lee; Adam Stooke; Lerrel Pinto; Pieter Abbeel; Aravind Srinivas (NeurIPS, 2020)

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning. - Younggyo Seo; Kimin Lee; Ignasi Clavera Gilaberte; Thanard Kurutach; Jinwoo Shin; Pieter Abbeel (NeurIPS, 2020)

Dynamics Generalization via Information Bottleneck in Deep Reinforcement Learning. - Xingyu Lu; Kimin Lee; Pieter Abbeel; Stas Tiomkin (CoRR, 2020)

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning. - Younggyo Seo; Kimin Lee; Ignasi Clavera; Thanard Kurutach; Jinwoo Shin; Pieter Abbeel (CoRR, 2020)

Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments. - Wilka Carvalho; Anthony Liang; Kimin Lee; Sungryull Sohn; Honglak Lee; Richard L. Lewis; Satinder Singh 001 (CoRR, 2020)

Dynamic Control for On-Demand Interference-Managed WLAN Infrastructures. - Seokhyun Kim; Kimin Lee; Yeonkeun Kim; Jinwoo Shin; Seungwon Shin 001; Song Chong (IEEE/ACM Trans. Netw., 2020)

MASKER: Masked Keyword Regularization for Reliable Text Classification. - Seung Jun Moon; Sangwoo Mo; Kimin Lee; Jaeho Lee 001; Jinwoo Shin (AAAI, 2021)

Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble. - Seunghyun Lee; Younggyo Seo; Kimin Lee; Pieter Abbeel; Jinwoo Shin (CoRL, 2021)

Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback. - Xiaofei Wang 008; Kimin Lee; Kourosh Hakhamaneshi; Pieter Abbeel; Michael Laskin (CoRL, 2021)

Learning to Sample with Local and Global Contexts in Experience Replay Buffer. - Youngmin Oh; Kimin Lee; Jinwoo Shin; Eunho Yang; Sung Ju Hwang (ICLR, 2021)

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. - Kimin Lee; Michael Laskin; Aravind Srinivas; Pieter Abbeel (ICML, 2021)

PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training. - Kimin Lee; Laura M. Smith; Pieter Abbeel (ICML, 2021)

State Entropy Maximization with Random Encoders for Efficient Exploration. - Younggyo Seo; Lili Chen; Jinwoo Shin; Honglak Lee; Pieter Abbeel; Kimin Lee (ICML, 2021)

Decoupling Representation Learning from Reinforcement Learning. - Adam Stooke; Kimin Lee; Pieter Abbeel; Michael Laskin (ICML, 2021)

Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment. - Wilka Carvalho; Anthony Liang; Kimin Lee; Sungryull Sohn; Honglak Lee; Richard L. Lewis; Satinder Singh 001 (IJCAI, 2021)

Decision Transformer: Reinforcement Learning via Sequence Modeling. - Lili Chen; Kevin Lu; Aravind Rajeswaran; Kimin Lee; Aditya Grover; Michael Laskin; Pieter Abbeel; Aravind Srinivas; Igor Mordatch (NeurIPS, 2021)

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. - Lili Chen; Kimin Lee; Aravind Srinivas; Pieter Abbeel (NeurIPS, 2021)

URLB: Unsupervised Reinforcement Learning Benchmark. - Michael Laskin; Denis Yarats; Hao Liu 055; Kimin Lee; Albert Zhan; Kevin Lu; Catherine Cang; Lerrel Pinto; Pieter Abbeel (NeurIPS Datasets and Benchmarks, 2021)

Improving Transferability of Representations via Augmentation-Aware Self-Supervision. - Hankook Lee; Kibok Lee 003; Kimin Lee; Honglak Lee; Jinwoo Shin (NeurIPS, 2021)

B-Pref: Benchmarking Preference-Based Reinforcement Learning. - Kimin Lee; Laura M. Smith; Anca D. Dragan; Pieter Abbeel (NeurIPS Datasets and Benchmarks, 2021)

Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments. - Abdus Salam Azad; Edward Kim 005; Qiancheng Wu; Kimin Lee; Ion Stoica; Pieter Abbeel; Sanjit A. Seshia (CoRR, 2021)

Programmatic Modeling and Generation of Real-Time Strategic Soccer Environments for Reinforcement Learning. - Abdus Salam Azad; Edward Kim 005; Qiancheng Wu; Kimin Lee; Ion Stoica; Pieter Abbeel; Alberto L. Sangiovanni-Vincentelli; Sanjit A. Seshia (AAAI, 2022)

Masked World Models for Visual Control. - Younggyo Seo; Danijar Hafner; Hao Liu 055; Fangchen Liu; Stephen James; Kimin Lee; Pieter Abbeel (CoRL, 2022)

HARP: Autoregressive Latent Video Prediction with High-Fidelity Image Generator. - Younggyo Seo; Kimin Lee; Fangchen Liu; Stephen James; Pieter Abbeel (ICIP, 2022)

Reward Uncertainty for Exploration in Preference-based Reinforcement Learning. - Xinran Liang; Katherine Shu; Kimin Lee; Pieter Abbeel (ICLR, 2022)

SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. - Jongjin Park; Younggyo Seo; Jinwoo Shin; Honglak Lee; Pieter Abbeel; Kimin Lee (ICLR, 2022)

Reinforcement Learning with Action-Free Pre-Training from Videos. - Younggyo Seo; Kimin Lee; Stephen James; Pieter Abbeel (ICML, 2022)

Towards More Generalizable One-shot Visual Imitation Learning. - Mandi Zhao; Fangchen Liu; Kimin Lee; Pieter Abbeel (ICRA, 2022)

Instruction-Following Agents with Jointly Pre-Trained Vision-Language Models. - Hao Liu 055; Lisa Lee; Kimin Lee; Pieter Abbeel (CoRR, 2022)

Preference Transformer: Modeling Human Preferences using Transformers for RL. - Changyeon Kim; Jongjin Park; Jinwoo Shin; Honglak Lee; Pieter Abbeel; Kimin Lee (ICLR, 2023)

Controllability-Aware Unsupervised Skill Discovery. - Seohong Park; Kimin Lee; Youngwoon Lee; Pieter Abbeel (ICML, 2023)

Multi-View Masked World Models for Visual Robotic Manipulation. - Younggyo Seo; Junsu Kim; Stephen James; Kimin Lee; Jinwoo Shin; Pieter Abbeel (ICML, 2023)

Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. - Ying Fan; Olivia Watkins; Yuqing Du; Hao Liu 055; Moonkyung Ryu; Craig Boutilier; Pieter Abbeel; Mohammad Ghavamzadeh; Kangwook Lee 001; Kimin Lee (NeurIPS, 2023)

Guide Your Agent with Adaptive Multimodal Rewards. - Changyeon Kim; Younggyo Seo; Hao Liu; Lisa Lee; Jinwoo Shin; Honglak Lee; Kimin Lee (NeurIPS, 2023)

StyleDrop: Text-to-Image Synthesis of Any Style. - Kihyuk Sohn; Lu Jiang 004; Jarred Barber; Kimin Lee; Nataniel Ruiz; Dilip Krishnan; Huiwen Chang; Yuanzhen Li; Irfan Essa; Michael Rubinstein; Yuan Hao; Glenn Entis; et al. (NeurIPS, 2023)

Aligning Text-to-Image Models using Human Feedback. - Kimin Lee; Hao Liu 055; Moonkyung Ryu; Olivia Watkins; Yuqing Du; Craig Boutilier; Pieter Abbeel; Mohammad Ghavamzadeh; Shixiang Shane Gu (CoRR, 2023)

DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. - Ying Fan; Olivia Watkins; Yuqing Du; Hao Liu 055; Moonkyung Ryu; Craig Boutilier; Pieter Abbeel; Mohammad Ghavamzadeh; Kangwook Lee 001; Kimin Lee (CoRR, 2023)

StyleDrop: Text-to-Image Generation in Any Style. - Kihyuk Sohn; Nataniel Ruiz; Kimin Lee; Daniel Castro Chin; Irina Blok; Huiwen Chang; Jarred Barber; Lu Jiang 004; Glenn Entis; Yuanzhen Li; Yuan Hao; Irfan Essa; et al. (CoRR, 2023)

InstructBooth: Instruction-following Personalized Text-to-Image Generation. - Daewon Chae; Nokyung Park; Jinkyu Kim; Kimin Lee (CoRR, 2023)

Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation. - Katherine M. Collins; Najoung Kim; Yonatan Bitton; Verena Rieser; Shayegan Omidshafiei; Yushi Hu; Sherol Chen; Senjuti Dutta; Minsuk Chang; Kimin Lee; Youwei Liang; Georgina Evans; et al. (AIES (1), 2024)

Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences. - Minyoung Hwang; Luca Weihs; Chanwoo Park; Kimin Lee; Aniruddha Kembhavi; Kiana Ehsani (CVPR, 2024)

Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback. - Kyuyoung Kim; Ah Jeong Seo; Hao Liu; Jinwoo Shin; Kimin Lee (EMNLP (Findings), 2024)

By My Eyes: Grounding Multimodal Large Language Models with Sensor Data via Visual Prompting. - Hyungjun Yoon; Biniyam Aschalew Tolera; Taesik Gong; Kimin Lee; Sung-Ju Lee (EMNLP, 2024)

Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models. - Kyuyoung Kim; Jongheon Jeong; Minyong An; Mohammad Ghavamzadeh; Krishnamurthy Dj Dvijotham; Jinwoo Shin; Kimin Lee (ICLR, 2024)

Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models. - Sangwon Jang; Jaehyeong Jo; Kimin Lee; Sung Ju Hwang (NeurIPS, 2024)

ADAPT^2: Adapting Pre-Trained Sensing Models to End-Users via Self-Supervision Replay. - Hyungjun Yoon; Jae Hyun Kwak; Biniyam Aschalew Tolera; Gaole Dai; Mo Li 001; Taesik Gong; Kimin Lee; Sung-Ju Lee (CoRR, 2024)

Benchmarking Mobile Device Control Agents across Diverse Configurations. - Juyong Lee; Taywon Min; Minyong An; Changyeon Kim; Kimin Lee (CoRR, 2024)

Aligning Large Language Models with Self-generated Preference Data. - Dongyoung Kim; Kimin Lee; Jinwoo Shin; Jaehyung Kim 001 (CoRR, 2024)

When LLMs Go Online: The Emerging Threat of Web-Enabled LLMs. - Hanna Kim; Minkyoo Song; Seung Ho Na; Seungwon Shin 001; Kimin Lee (CoRR, 2024)

MobileSafetyBench: Evaluating Safety of Autonomous Agents in Mobile Device Control. - Juyong Lee; Dongyoon Hahm; June Suk Choi; W. Bradley Knox; Kimin Lee (CoRR, 2024)

Improbable Bigrams Expose Vulnerabilities of Incomplete Tokens in Byte-Level Tokenizers. - Eugene Jang; Kimin Lee; Jin-Woo Chung; Keuntae Park; Seungwon Shin 001 (CoRR, 2024)

DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models. - Daewon Chae; June Suk Choi; Jinkyu Kim; Kimin Lee (AAAI, 2025)

What Really Matters in Many-Shot Attacks? An Empirical Study of Long-Context Vulnerabilities in LLMs. - Sangyeop Kim 001; Yohan Lee; Yongwoo Song; Kimin Lee (ACL (1), 2025)

Enhancing LLM Agent Safety via Causal Influence Prompting. - Dongyoon Hahm; Woogyeol Jin; June Suk Choi; Sungsoo Ahn; Kimin Lee (ACL (Findings), 2025)

Understanding Impact of Human Feedback via Influence Functions. - Taywon Min; Haeone Lee; Yongchan Kwon; Kimin Lee (ACL (1), 2025)

Silent Branding Attack: Trigger-free Data Poisoning Attack on Text-to-Image Diffusion Models. - Sangwon Jang; June Suk Choi; Jaehyeong Jo; Kimin Lee; Sung Ju Hwang (CVPR, 2025)

DiffusionGuard: A Robust Defense Against Malicious Diffusion-based Image Editing. - June Suk Choi; Kyungmin Lee; Jongheon Jeong; Saining Xie; Jinwoo Shin; Kimin Lee (ICLR, 2025)

Subtask-Aware Visual Reward Learning from Segmented Demonstrations. - Changyeon Kim; Minho Heo; Doohyun Lee; Honglak Lee; Jinwoo Shin; Joseph J. Lim; Kimin Lee (ICLR, 2025)

Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment. - Dongyoung Kim; Kimin Lee; Jinwoo Shin; Jaehyung Kim 001 (ICLR, 2025)

Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents. - Dongjun Lee; Juyong Lee; Kyuyoung Kim; Jihoon Tack; Jinwoo Shin; Yee Whye Teh; Kimin Lee (ICLR, 2025)

Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models. - Yongjin Yang; Sihyeon Kim; Hojung Jung; Sangmin Bae; SangMook Kim; Se-Young Yun; Kimin Lee (ICLR, 2025)

Latent Action Pretraining from Videos. - Seonghyeon Ye; Joel Jang; Byeongguk Jeon; Se June Joo; Jianwei Yang; Baolin Peng; Ajay Mandlekar; Reuben Tan; Yu-Wei Chao; Bill Yuchen Lin; Lars Liden; Kimin Lee; et al. (ICLR, 2025)

SelfReplay: Adapting Self-Supervised Sensory Models via Adaptive Meta-Task Replay. - Hyungjun Yoon; Jae Hyun Kwak; Biniyam Aschalew Tolera; Gaole Dai; Mo Li 001; Taesik Gong; Kimin Lee; Sung-Ju Lee (SenSys, 2025)

Understanding Impact of Human Feedback via Influence Functions. - Taywon Min; Haeone Lee; Hanho Ryu; Yongchan Kwon; Kimin Lee (CoRR, 2025)

Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness. - Yongjin Yang; Euiin Yi; Jongwoo Ko; Kimin Lee; Zhijing Jin 001; Se-Young Yun (CoRR, 2025)

Automated Skill Discovery for Language Agents through Exploration and Iterative Feedback. - Yongjin Yang; Sinjae Kang; Juyong Lee; Dongjun Lee; Se-Young Yun; Kimin Lee (CoRR, 2025)

Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search. - Dongryung Lee; Se June Joo; Kimin Lee; Beomjoon Kim (CoRR, 2025)

Enhancing Motion Dynamics of Image-to-Video Models via Adaptive Low-Pass Guidance. - June Suk Choi; Kyungmin Lee; Sihyun Yu; Yisol Choi; Jinwoo Shin; Kimin Lee (CoRR, 2025)

Unintended Misalignment from Agentic Fine-Tuning: Risks and Mitigation. - Dongyoon Hahm; Taywon Min; Woogyeol Jin; Kimin Lee (CoRR, 2025)