Kimin Lee

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 97

Top Topics

Image Generation

Reinforcement Learning

Unified Framework

Top Venues

Publications

Dongyoung Kim, Kimin Lee, Jinwoo Shin, Jaehyung Kim
Aligning Large Language Models with Self-generated Preference Data. CoRR (2024)
Juyong Lee, Taywon Min, Minyong An, Changyeon Kim, Kimin Lee
Benchmarking Mobile Device Control Agents across Diverse Configurations. CoRR (2024)
Hyungjun Yoon, Biniyam Aschalew Tolera, Taesik Gong, Kimin Lee, Sung-Ju Lee
By My Eyes: Grounding Multimodal Large Language Models with Sensor Data via Visual Prompting. CoRR (2024)
Hyungjun Yoon, Jae Hyun Kwak, Biniyam Aschalew Tolera, Gaole Dai, Mo Li, Taesik Gong, Kimin Lee, Sung-Ju Lee
ADAPT^2: Adapting Pre-Trained Sensing Models to End-Users via Self-Supervision Replay. CoRR (2024)
Sangwon Jang, Jaehyeong Jo, Kimin Lee, Sung Ju Hwang
Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models. CoRR (2024)
Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dj Dvijotham, Jinwoo Shin, Kimin Lee
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models. ICLR (2024)
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, Sahil Singla, Gang Li, Adrian Weller, Junfeng He, Deepak Ramachandran, Krishnamurthy Dj Dvijotham
Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation. CoRR (2024)
Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dvijotham, Jinwoo Shin, Kimin Lee
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models. CoRR (2024)
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. CoRR (2023)
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. NeurIPS (2023)
Younggyo Seo, Junsu Kim, Stephen James, Kimin Lee, Jinwoo Shin, Pieter Abbeel
Multi-View Masked World Models for Visual Robotic Manipulation. ICML (2023)
Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee
Guide Your Agent with Adaptive Multimodal Rewards. NeurIPS (2023)
Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
Preference Transformer: Modeling Human Preferences using Transformers for RL. CoRR (2023)
Seohong Park, Kimin Lee, Youngwoon Lee, Pieter Abbeel
Controllability-Aware Unsupervised Skill Discovery. ICML (2023)
Younggyo Seo, Junsu Kim, Stephen James, Kimin Lee, Jinwoo Shin, Pieter Abbeel
Multi-View Masked World Models for Visual Robotic Manipulation. CoRR (2023)
Kihyuk Sohn, Lu Jiang, Jarred Barber, Kimin Lee, Nataniel Ruiz, Dilip Krishnan, Huiwen Chang, Yuanzhen Li, Irfan Essa, Michael Rubinstein, Yuan Hao, Glenn Entis, Irina Blok, Daniel Castro Chin
StyleDrop: Text-to-Image Synthesis of Any Style. NeurIPS (2023)
Minyoung Hwang, Luca Weihs, Chanwoo Park, Kimin Lee, Aniruddha Kembhavi, Kiana Ehsani
Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences. CoRR (2023)
Daewon Chae, Nokyung Park, Jinkyu Kim, Kimin Lee
InstructBooth: Instruction-following Personalized Text-to-Image Generation. CoRR (2023)
Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee
Guide Your Agent with Adaptive Multimodal Rewards. CoRR (2023)
Kihyuk Sohn, Nataniel Ruiz, Kimin Lee, Daniel Castro Chin, Irina Blok, Huiwen Chang, Jarred Barber, Lu Jiang, Glenn Entis, Yuanzhen Li, Yuan Hao, Irfan Essa, Michael Rubinstein, Dilip Krishnan
StyleDrop: Text-to-Image Generation in Any Style. CoRR (2023)
Seohong Park, Kimin Lee, Youngwoon Lee, Pieter Abbeel
Controllability-Aware Unsupervised Skill Discovery. CoRR (2023)
Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
Preference Transformer: Modeling Human Preferences using Transformers for RL. ICLR (2023)
Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Shixiang Shane Gu
Aligning Text-to-Image Models using Human Feedback. CoRR (2023)
Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. ICLR (2022)
Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. CoRR (2022)
Abdus Salam Azad, Edward Kim, Qiancheng Wu, Kimin Lee, Ion Stoica, Pieter Abbeel, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia
Programmatic Modeling and Generation of Real-Time Strategic Soccer Environments for Reinforcement Learning. AAAI (2022)
Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel
Masked World Models for Visual Control. CoRL (2022)
Younggyo Seo, Kimin Lee, Fangchen Liu, Stephen James, Pieter Abbeel
HARP: Autoregressive Latent Video Prediction with High-Fidelity Image Generator. ICIP (2022)
Younggyo Seo, Kimin Lee, Fangchen Liu, Stephen James, Pieter Abbeel
HARP: Autoregressive Latent Video Prediction with High-Fidelity Image Generator. CoRR (2022)
Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel
Reward Uncertainty for Exploration in Preference-based Reinforcement Learning. CoRR (2022)
Mandi Zhao, Fangchen Liu, Kimin Lee, Pieter Abbeel
Towards More Generalizable One-shot Visual Imitation Learning. ICRA (2022)
Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel
Reward Uncertainty for Exploration in Preference-based Reinforcement Learning. ICLR (2022)
Hao Liu, Lisa Lee, Kimin Lee, Pieter Abbeel
Instruction-Following Agents with Jointly Pre-Trained Vision-Language Models. CoRR (2022)
Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel
Masked World Models for Visual Control. CoRR (2022)
Younggyo Seo, Kimin Lee, Stephen James, Pieter Abbeel
Reinforcement Learning with Action-Free Pre-Training from Videos. CoRR (2022)
Younggyo Seo, Kimin Lee, Stephen L. James, Pieter Abbeel
Reinforcement Learning with Action-Free Pre-Training from Videos. ICML (2022)
Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin
Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback. CoRR (2021)
Kimin Lee, Laura M. Smith, Anca D. Dragan, Pieter Abbeel
B-Pref: Benchmarking Preference-Based Reinforcement Learning. NeurIPS Datasets and Benchmarks (2021)
Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. NeurIPS (2021)
Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel
URLB: Unsupervised Reinforcement Learning Benchmark. CoRR (2021)
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
State Entropy Maximization with Random Encoders for Efficient Exploration. ICML (2021)
Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment. IJCAI (2021)
Seunghyun Lee, Younggyo Seo, Kimin Lee, Pieter Abbeel, Jinwoo Shin
Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble. CoRR (2021)
Abdus Salam Azad, Edward Kim, Qiancheng Wu, Kimin Lee, Ion Stoica, Pieter Abbeel, Sanjit A. Seshia
Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments. CoRR (2021)
Seunghyun Lee, Younggyo Seo, Kimin Lee, Pieter Abbeel, Jinwoo Shin
Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble. CoRL (2021)
Kimin Lee, Laura M. Smith, Pieter Abbeel
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training. ICML (2021)
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
Decision Transformer: Reinforcement Learning via Sequence Modeling. NeurIPS (2021)
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
State Entropy Maximization with Random Encoders for Efficient Exploration. CoRR (2021)
Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel
URLB: Unsupervised Reinforcement Learning Benchmark. NeurIPS Datasets and Benchmarks (2021)
Seung Jun Moon, Sangwoo Mo, Kimin Lee, Jaeho Lee, Jinwoo Shin
MASKER: Masked Keyword Regularization for Reliable Text Classification. AAAI (2021)
Kimin Lee, Laura Smith, Anca D. Dragan, Pieter Abbeel
B-Pref: Benchmarking Preference-Based Reinforcement Learning. CoRR (2021)
Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings. CoRR (2021)
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
Decision Transformer: Reinforcement Learning via Sequence Modeling. CoRR (2021)
Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin
Improving Transferability of Representations via Augmentation-Aware Self-Supervision. NeurIPS (2021)
Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin
Improving Transferability of Representations via Augmentation-Aware Self-Supervision. CoRR (2021)
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Decoupling Representation Learning from Reinforcement Learning. ICML (2021)
Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin
Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback. CoRL (2021)
Mandi Zhao, Fangchen Liu, Kimin Lee, Pieter Abbeel
Towards More Generalizable One-shot Visual Imitation Learning. CoRR (2021)
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. ICML (2021)
Kimin Lee, Laura M. Smith, Pieter Abbeel
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training. CoRR (2021)
Youngmin Oh, Kimin Lee, Jinwoo Shin, Eunho Yang, Sung Ju Hwang
Learning to Sample with Local and Global Contexts in Experience Replay Buffer. ICLR (2021)
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
Reinforcement Learning with Augmented Data. CoRR (2020)
Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
Reinforcement Learning with Augmented Data. NeurIPS (2020)
Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning. ICML (2020)
Younggyo Seo, Kimin Lee, Ignasi Clavera, Thanard Kurutach, Jinwoo Shin, Pieter Abbeel
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning. CoRR (2020)
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. CoRR (2020)
Sukmin Yun, Jongjin Park, Kimin Lee, Jinwoo Shin
Regularizing Class-wise Predictions via Self-knowledge Distillation. CoRR (2020)
Younggyo Seo, Kimin Lee, Ignasi Clavera Gilaberte, Thanard Kurutach, Jinwoo Shin, Pieter Abbeel
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning. NeurIPS (2020)
Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments. CoRR (2020)
Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning. CoRR (2020)
Youngmin Oh, Kimin Lee, Jinwoo Shin, Eunho Yang, Sung Ju Hwang
Learning to Sample with Local and Global Contexts in Experience Replay Buffer. CoRR (2020)
Sukmin Yun, Jongjin Park, Kimin Lee, Jinwoo Shin
Regularizing Class-Wise Predictions via Self-Knowledge Distillation. CVPR (2020)
Seung Jun Moon, Sangwoo Mo, Kimin Lee, Jaeho Lee, Jinwoo Shin
MASKER: Masked Keyword Regularization for Reliable Text Classification. CoRR (2020)
Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee
Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning. ICLR (2020)
Xingyu Lu, Kimin Lee, Pieter Abbeel, Stas Tiomkin
Dynamics Generalization via Information Bottleneck in Deep Reinforcement Learning. CoRR (2020)
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Decoupling Representation Learning from Reinforcement Learning. CoRR (2020)
Seokhyun Kim, Kimin Lee, Yeonkeun Kim, Jinwoo Shin, Seungwon Shin, Song Chong
Dynamic Control for On-Demand Interference-Managed WLAN Infrastructures. IEEE/ACM Trans. Netw. 28 (1) (2020)
Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee
Incremental Learning with Unlabeled Data in the Wild. CVPR Workshops (2019)
Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee
Incremental Learning with Unlabeled Data in the Wild. CoRR (2019)
Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin
Robust Inference via Generative Classifiers for Handling Noisy Labels. CoRR (2019)
Dan Hendrycks, Kimin Lee, Mantas Mazeika
Using Pre-Training Can Improve Model Robustness and Uncertainty. ICML (2019)
Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee
Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild. ICCV (2019)
Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee
A Simple Randomization Technique for Generalization in Deep Reinforcement Learning. CoRR (2019)
Dan Hendrycks, Kimin Lee, Mantas Mazeika
Using Pre-Training Can Improve Model Robustness and Uncertainty. CoRR (2019)
Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin
Robust Inference via Generative Classifiers for Handling Noisy Labels. ICML (2019)
Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples. ICLR (Poster) (2018)
Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. NeurIPS (2018)
Jonghwan Mun, Kimin Lee, Jinwoo Shin, Bohyung Han
Learning to Specialize with Knowledge Distillation for Visual Question Answering. NeurIPS (2018)
Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee
Hierarchical Novelty Detection for Visual Object Recognition. CVPR (2018)
Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. CoRR (2018)
Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee
Hierarchical Novelty Detection for Visual Object Recognition. CoRR (2018)
Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples. CoRR (2017)
Kimin Lee, Jaehyung Kim, Song Chong, Jinwoo Shin
Simplified Stochastic Feedforward Neural Networks. CoRR (2017)
Kimin Lee, Changho Hwang, KyoungSoo Park, Jinwoo Shin
Confident Multiple Choice Learning. ICML (2017)
Kimin Lee, Changho Hwang, KyoungSoo Park, Jinwoo Shin
Confident Multiple Choice Learning. CoRR (2017)
Kimin Lee, Yeonkeun Kim, Seokhyun Kim, Jinwoo Shin, Seungwon Shin, Song Chong
Just-in-time WLANs: On-demand interference-managed WLAN infrastructures. INFOCOM (2016)
Jaeseong Jeong, Kyunghan Lee, Beknazar Abdikamalov, Kimin Lee, Song Chong
TravelMiner: On the Benefit of Path-Based Mobility Prediction. SECON (2016)