Spam Deobfuscation using a Hidden Markov Model. - Honglak Lee; Andrew Y. Ng (CEAS, 2005)

Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes. - Erick Delage; Honglak Lee; Andrew Y. Ng (ISRR, 2005)

Efficient L1 Regularized Logistic Regression. - Su-In Lee; Honglak Lee; Pieter Abbeel; Andrew Y. Ng (AAAI, 2006)

A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image. - Erick Delage; Honglak Lee; Andrew Y. Ng (CVPR (2), 2006)

Quadruped Robot Obstacle Negotiation via Reinforcement Learning. - Honglak Lee; Yirong Shen; Chih-Han Yu; Gurjeet Singh; Andrew Y. Ng (ICRA, 2006)

Efficient sparse coding algorithms. - Honglak Lee; Alexis J. Battle; Rajat Raina; Andrew Y. Ng (NIPS, 2006)

Self-taught learning: transfer learning from unlabeled data. - Rajat Raina; Alexis J. Battle; Honglak Lee; Benjamin Packer; Andrew Y. Ng (ICML, 2007)

Sparse deep belief net model for visual area V2. - Honglak Lee; Chaitanya Ekanadham; Andrew Y. Ng (NIPS, 2007)

Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. - Honglak Lee; Roger B. Grosse; Rajesh Ranganath; Andrew Y. Ng (ICML, 2009)

Exponential Family Sparse Coding with Application to Self-taught Learning. - Honglak Lee; Rajat Raina; Alex Teichman; Andrew Y. Ng (IJCAI, 2009)

Measuring Invariances in Deep Networks. - Ian J. Goodfellow; Quoc V. Le; Andrew M. Saxe; Honglak Lee; Andrew Y. Ng (NIPS, 2009)

Unsupervised feature learning for audio classification using convolutional deep belief networks. - Honglak Lee; Peter T. Pham; Yan Largman; Andrew Y. Ng (NIPS, 2009)

An integrated machine learning approach to stroke prediction. - Aditya Khosla; Yu Cao; Cliff Chiung-Yu Lin; Hsu-Kuang Chiu; Junling Hu; Honglak Lee (KDD, 2010)

Unsupervised feature learning via sparse hierarchical representations. - Honglak Lee (2010)

Efficient learning of sparse, distributed, convolutional feature representations for object recognition. - Kihyuk Sohn; Dae Yon Jung; Honglak Lee; Alfred O. Hero III (ICCV, 2011)

Multimodal Deep Learning. - Jiquan Ngiam; Aditya Khosla; Mingyu Kim; Juhan Nam; Honglak Lee; Andrew Y. Ng (ICML, 2011)

A Classification-Based Polyphonic Piano Transcription Approach Using Learned Feature Representations. - Juhan Nam; Jiquan Ngiam; Honglak Lee; Malcolm Slaney (ISMIR, 2011)

Unsupervised learning of hierarchical representations with convolutional deep belief networks. - Honglak Lee; Roger B. Grosse; Rajesh Ranganath; Andrew Y. Ng (Commun. ACM, 2011)

An Analysis of Single-Layer Networks in Unsupervised Feature Learning. - Adam Coates 002; Andrew Y. Ng; Honglak Lee (AISTATS, 2011)

Learning hierarchical representations for face verification with convolutional deep belief networks. - Gary B. Huang; Honglak Lee; Erik G. Learned-Miller (CVPR, 2012)

An efficient branch-and-bound algorithm for optimal human pose estimation. - Min Sun 001; Murali Telaprolu; Honglak Lee; Silvio Savarese (CVPR, 2012)

Learning Invariant Representations with Local Transformations. - Kihyuk Sohn; Honglak Lee (ICML, 2012)

Learning to Align from Scratch. - Gary B. Huang; Marwan A. Mattar; Honglak Lee; Erik G. Learned-Miller (NIPS, 2012)

Efficient and Exact MAP-MRF Inference using Branch and Bound. - Min Sun 001; Murali Telaprolu; Honglak Lee; Silvio Savarese (AISTATS, 2012)

Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers. - Caoxie Zhang; Honglak Lee; Kang G. Shin (AISTATS, 2012)

Online Incremental Feature Learning with Denoising Autoencoders. - Guanyu Zhou; Kihyuk Sohn; Honglak Lee (AISTATS, 2012)

Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling. - Andrew Kae; Kihyuk Sohn; Honglak Lee; Erik G. Learned-Miller (CVPR, 2013)

Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines. - Roni Mittelman; Honglak Lee; Benjamin Kuipers; Silvio Savarese (CVPR, 2013)

Deep learning for robust feature generation in audiovisual emotion recognition. - Yelin Kim; Honglak Lee; Emily Mower Provost (ICASSP, 2013)

Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines. - Kihyuk Sohn; Guanyu Zhou; Chansoo Lee; Honglak Lee (ICML (2), 2013)

Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising. - Forest Agostinelli; Michael R. Anderson; Honglak Lee (NIPS, 2013)

Guest Editors' Introduction: Special Section on Learning Deep Architectures. - Samy Bengio; Li Deng 001; Hugo Larochelle; Honglak Lee; Ruslan Salakhutdinov (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Structured Recurrent Temporal Restricted Boltzmann Machines. - Roni Mittelman; Benjamin Kuipers; Silvio Savarese; Honglak Lee (ICML, 2014)

Learning to Disentangle Factors of Variation with Manifold Interaction. - Scott E. Reed; Kihyuk Sohn; Yuting Zhang 001; Honglak Lee (ICML, 2014)

Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning. - Xiaoxiao Guo; Satinder Singh 001; Honglak Lee; Richard L. Lewis; Xiaoshi Wang (NIPS, 2014)

Improved Multimodal Deep Learning with Variation of Information. - Kihyuk Sohn; Wenling Shang; Honglak Lee (NIPS, 2014)

Zero-Shot Learning with Structured Embeddings. - Zeynep Akata; Honglak Lee; Bernt Schiele (CoRR, 2014)

Evaluation of output embeddings for fine-grained image classification. - Zeynep Akata; Scott E. Reed; Daniel Walter; Honglak Lee; Bernt Schiele (CVPR, 2015)

Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction. - Yuting Zhang 001; Kihyuk Sohn; Ruben Villegas; Gang Pan 001; Honglak Lee (CVPR, 2015)

A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks. - Changhan Wang; Xinchen Yan; Max Smith; Kanika Kochhar; Marcie Rubin; Stephen M. Warren; James S. Wrobel; Honglak Lee (EMBC, 2015)

Action-Conditional Video Prediction using Deep Networks in Atari Games. - Junhyuk Oh; Xiaoxiao Guo; Honglak Lee; Richard L. Lewis; Satinder Singh 001 (NIPS, 2015)

Deep Visual Analogy-Making. - Scott E. Reed; Yi Zhang; Yuting Zhang 001; Honglak Lee (NIPS, 2015)

Learning Structured Output Representation using Deep Conditional Generative Models. - Kihyuk Sohn; Honglak Lee; Xinchen Yan (NIPS, 2015)

Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis. - Jimei Yang; Scott E. Reed; Ming-Hsuan Yang 001; Honglak Lee (NIPS, 2015)

Training Deep Neural Networks on Noisy Labels with Bootstrapping. - Scott E. Reed; Honglak Lee; Dragomir Anguelov; Christian Szegedy; Dumitru Erhan; Andrew Rabinovich (ICLR (Workshop), 2015)

Deep learning for detecting robotic grasps. - Ian Lenz; Honglak Lee; Ashutosh Saxena (Int. J. Robotics Res., 2015)

Editorial introduction to the Neural Networks special issue on Deep Learning of Representations. - Yoshua Bengio; Honglak Lee (Neural Networks, 2015)

Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. - Seunghoon Hong; Junhyuk Oh; Honglak Lee; Bohyung Han (CVPR, 2016)

Learning Deep Representations of Fine-Grained Visual Descriptions. - Scott E. Reed; Zeynep Akata; Honglak Lee; Bernt Schiele (CVPR, 2016)

Object Contour Detection with a Fully Convolutional Encoder-Decoder Network. - Jimei Yang; Brian L. Price; Scott Cohen; Honglak Lee; Ming-Hsuan Yang 001 (CVPR, 2016)

Attribute2Image: Conditional Image Generation from Visual Attributes. - Xinchen Yan; Jimei Yang; Kihyuk Sohn; Honglak Lee (ECCV (4), 2016)

Control of Memory, Active Perception, and Action in Minecraft. - Junhyuk Oh; Valliappa Chockalingam; Satinder Singh 001; Honglak Lee (ICML, 2016)

Generative Adversarial Text to Image Synthesis. - Scott E. Reed; Zeynep Akata; Xinchen Yan; Lajanugen Logeswaran; Bernt Schiele; Honglak Lee (ICML, 2016)

Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units. - Wenling Shang; Kihyuk Sohn; Diogo Almeida; Honglak Lee (ICML, 2016)

Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification. - Yuting Zhang 001; Kibok Lee 003; Honglak Lee (ICML, 2016)

Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games. - Xiaoxiao Guo; Satinder Singh 001; Richard L. Lewis; Honglak Lee (IJCAI, 2016)

Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents. - Rui Zhang 037; Honglak Lee; Dragomir R. Radev (HLT-NAACL, 2016)

Learning What and Where to Draw. - Scott E. Reed; Zeynep Akata; Santosh Mohan; Samuel Tenka; Bernt Schiele; Honglak Lee (NIPS, 2016)

Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision. - Xinchen Yan; Jimei Yang; Ersin Yumer; Yijie Guo; Honglak Lee (NIPS, 2016)

Discriminative Training of Structured Dictionaries via Block Orthogonal Matching Pursuit. - Wenling Shang; Kihyuk Sohn; Honglak Lee; Anna C. Gilbert (SDM, 2016)

Sentence Ordering using Recurrent Neural Networks. - Lajanugen Logeswaran; Honglak Lee; Dragomir R. Radev (CoRR, 2016)

Deep Variational Canonical Correlation Analysis. - Weiran Wang; Honglak Lee; Karen Livescu (CoRR, 2016)

Exploring the structure of a real-time, arbitrary neural artistic stylization network. - Golnaz Ghiasi; Honglak Lee; Manjunath Kudlur; Vincent Dumoulin; Jonathon Shlens (BMVC, 2017)

Weakly Supervised Semantic Segmentation Using Web-Crawled Videos. - Seunghoon Hong; Donghun Yeo; Suha Kwak; Honglak Lee; Bohyung Han (CVPR, 2017)

Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries. - Yuting Zhang 001; Luyao Yuan; Yijie Guo; Zhiyuan He 003; I-An Huang; Honglak Lee (CVPR, 2017)

Decomposing Motion and Content for Natural Video Sequence Prediction. - Ruben Villegas; Jimei Yang; Seunghoon Hong; Xunyu Lin; Honglak Lee (ICLR (Poster), 2017)

Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. - Junhyuk Oh; Satinder Singh 001; Honglak Lee; Pushmeet Kohli (ICML, 2017)

Learning to Generate Long-term Future via Hierarchical Prediction. - Ruben Villegas; Jimei Yang; Yuliang Zou; Sungryull Sohn; Xunyu Lin; Honglak Lee (ICML, 2017)

Towards Understanding the Invertibility of Convolutional Neural Networks. - Anna C. Gilbert; Yi Zhang; Kibok Lee 003; Yuting Zhang 001; Honglak Lee (IJCAI, 2017)

Value Prediction Network. - Junhyuk Oh; Satinder Singh 001; Honglak Lee (NIPS, 2017)

Learning Grasping Interaction with Geometry-aware 3D Representations. - Xinchen Yan; Mohi Khansari; Yunfei Bai; Jasmine Hsu; Arkanath Pathak; Abhinav Gupta 001; James Davidson; Honglak Lee (CoRR, 2017)

Sentence Ordering and Coherence Modeling using Recurrent Neural Networks. - Lajanugen Logeswaran; Honglak Lee; Dragomir R. Radev (AAAI, 2018)

Addressee and Response Selection in Multi-Party Conversations With Speaker Interaction RNNs. - Rui Zhang 037; Honglak Lee; Lazaros Polymenakos; Dragomir R. Radev (AAAI, 2018)

Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis. - Seunghoon Hong; Dingdong Yang; Jongwook Choi; Honglak Lee (CVPR, 2018)

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

Neural Kinematic Networks for Unsupervised Motion Retargetting. - Ruben Villegas; Jimei Yang; Duygu Ceylan; Honglak Lee (CVPR, 2018)

Unsupervised Discovery of Object Landmarks as Structural Representations. - Yuting Zhang 001; Yijie Guo; Yixin Jin; Yijun Luo; Zhiyuan He 003; Honglak Lee (CVPR, 2018)

MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics. - Xinchen Yan; Akash Rastogi; Ruben Villegas; Kalyan Sunkavalli; Eli Shechtman; Sunil Hadap; Ersin Yumer; Honglak Lee (ECCV (5), 2018)

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

An efficient framework for learning sentence representations. - Lajanugen Logeswaran; Honglak Lee (ICLR (Poster), 2018)

Self-Imitation Learning. - Junhyuk Oh; Yijie Guo; Satinder Singh 001; Honglak Lee (ICML, 2018)

Hierarchical Long-term Video Prediction without Supervision. - Nevan Wichers; Ruben Villegas; Dumitru Erhan; Honglak Lee (ICML, 2018)

Learning 6-DOF Grasping Interaction via Deep Geometry-Aware 3D Representations. - Xinchen Yan; Jasmine Hsu; Mohammad Khansari 002; Yunfei Bai; Arkanath Pathak; Abhinav Gupta 001; James Davidson; Honglak Lee (ICRA, 2018)

Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion. - Jacob Buckman; Danijar Hafner; George Tucker; Eugene Brevdo; Honglak Lee (NeurIPS, 2018)

Learning Hierarchical Semantic Image Manipulation through Structured Representations. - Seunghoon Hong; Xinchen Yan; Thomas E. Huang; Honglak Lee (NeurIPS, 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)

Content preserving text generation with attribute controls. - Lajanugen Logeswaran; Honglak Lee; Samy Bengio (NeurIPS, 2018)

Data-Efficient Hierarchical Reinforcement Learning. - Ofir Nachum; Shixiang Gu; Honglak Lee; Sergey Levine (NeurIPS, 2018)

Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. - Sungryull Sohn; Junhyuk Oh; Honglak Lee (NeurIPS, 2018)

Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. - Sungryull Sohn; Junhyuk Oh; Honglak Lee (CoRR, 2018)

Generative Adversarial Self-Imitation Learning. - Yijie Guo; Junhyuk Oh; Satinder Singh 001; Honglak Lee (CoRR, 2018)

Zero-Shot Entity Linking by Reading Entity Descriptions. - Lajanugen Logeswaran; Ming-Wei Chang; Kenton Lee; Kristina Toutanova; Jacob Devlin; Honglak Lee (ACL (1), 2019)

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

Adversarial Defense via Learning to Generate Diverse Attacks. - Yunseok Jang 001; Tianchen Zhao; Seunghoon Hong; Honglak Lee (ICCV, 2019)

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

Contingency-Aware Exploration in Reinforcement Learning. - Jongwook Choi; Yijie Guo; Marcin Moczulski; Junhyuk Oh; Neal Wu; Mohammad Norouzi 002; Honglak Lee (ICLR (Poster), 2019)

Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. - Ofir Nachum; Shixiang Gu; Honglak Lee; Sergey Levine (ICLR (Poster), 2019)

Diversity-Sensitive Conditional Generative Adversarial Networks. - Dingdong Yang; Seunghoon Hong; Yunseok Jang 001; Tianchen Zhao; Honglak Lee (ICLR (Poster), 2019)

Learning Latent Dynamics for Planning from Pixels. - Danijar Hafner; Timothy P. Lillicrap; Ian Fischer; Ruben Villegas; David Ha; Honglak Lee; James Davidson (ICML, 2019)

Similarity of Neural Network Representations Revisited. - Simon Kornblith; Mohammad Norouzi 002; Honglak Lee; Geoffrey E. Hinton (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)

Unsupervised learning of object structure and dynamics from videos. - Matthias Minderer; Chen Sun 002; Ruben Villegas; Forrester Cole; Kevin P. Murphy; Honglak Lee (NeurIPS, 2019)

High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks. - Ruben Villegas; Arkanath Pathak; Harini Kannan; Dumitru Erhan; Quoc V. Le; Honglak Lee (NeurIPS, 2019)

SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing. - Haonan Qiu; Chaowei Xiao; Lei Yang; Xinchen Yan; Honglak Lee; Bo Li 026 (CoRR, 2019)

Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks. - Xinchen Yan; Mohi Khansari; Jasmine Hsu; Yuanzheng Gong; Yunfei Bai; Sören Pirk; Honglak Lee (CoRR, 2019)

Efficient Exploration with Self-Imitation Learning via Trajectory-Conditioned Policy. - Yijie Guo; Jongwook Choi; Marcin Moczulski; Samy Bengio; Mohammad Norouzi 002; Honglak Lee (CoRR, 2019)

Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? - Ofir Nachum; Haoran Tang; Xingyu Lu; Shixiang Gu; Honglak Lee; Sergey Levine (CoRR, 2019)

IEG: Robust Neural Network Training to Tackle Severe Label Noise. - Zizhao Zhang; Han Zhang 010; Sercan Ömer Arik; Honglak Lee; Tomas Pfister (CoRR, 2019)

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

Interpretable Text-to-Image Synthesis with Hierarchical Semantic Layout Generation. - Seunghoon Hong; Dingdong Yang; Jongwook Choi; Honglak Lee (Explainable AI, 2019)

How Should an Agent Practice? - Janarthanan Rajendran; Richard L. Lewis; Vivek Veeriah; Honglak Lee; Satinder Singh 001 (AAAI, 2020)

Distilling Effective Supervision From Severe Label Noise. - Zizhao Zhang; Han Zhang 010; Sercan Ömer Arik; Honglak Lee; Tomas Pfister (CVPR, 2020)

Efficient Adversarial Training With Transferable Adversarial Examples. - Haizhong Zheng; Ziqi Zhang 004; Juncheng Gu; Honglak Lee; Atul Prakash 001 (CVPR, 2020)

High-Fidelity Synthesis with Disentangled Representation. - Wonkwang Lee; Donggyun Kim; Seunghoon Hong; Honglak Lee (ECCV (26), 2020)

SemanticAdv: Generating Adversarial Examples via Attribute-Conditioned Image Editing. - Haonan Qiu; Chaowei Xiao; Lei Yang; Xinchen Yan; Honglak Lee; Bo Li 026 (ECCV (14), 2020)

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

Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies. - Sungryull Sohn; Hyunjae Woo; Jongwook Choi; Honglak Lee (ICLR, 2020)

Consistency Regularization for Generative Adversarial Networks. - Han Zhang 010; Zizhao Zhang; Augustus Odena; 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)

BRPO: Batch Residual Policy Optimization. - Sungryull Sohn; Yinlam Chow; Jayden Ooi; Ofir Nachum; Honglak Lee; Ed H. Chi; Craig Boutilier (IJCAI, 2020)

Ode to an ODE. - Krzysztof Marcin Choromanski; Jared Quincy Davis; Valerii Likhosherstov; Xingyou Song; Jean-Jacques E. Slotine; Jacob Varley; Honglak Lee; Adrian Weller; Vikas Sindhwani (NeurIPS, 2020)

Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards. - Yijie Guo; Jongwook Choi; Marcin Moczulski; Shengyu Feng; Samy Bengio; Mohammad Norouzi 002; Honglak Lee (NeurIPS, 2020)

Predictive Information Accelerates Learning in RL. - Kuang-Huei Lee; Ian Fischer; Anthony Z. Liu; Yijie Guo; Honglak Lee; John F. Canny; Sergio Guadarrama (NeurIPS, 2020)

Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning. - Guangxiang Zhu; Minghao Zhang; Honglak Lee; Chongjie Zhang (NeurIPS, 2020)

CompressNet: Generative Compression at Extremely Low Bitrates. - Shubham Dash; Giridharan Kumaravelu; Vijayakrishna Naganoor; Suraj Kiran Raman; Aditya Ramesh; Honglak Lee (WACV, 2020)

Time Dependence in Non-Autonomous Neural ODEs. - Jared Quincy Davis; Krzysztof Choromanski; Jake Varley; Honglak Lee; Jean-Jacques E. Slotine; Valerii Likhosterov; Adrian Weller; Ameesh Makadia; Vikas Sindhwani (CoRR, 2020)

An Ode to an ODE. - Krzysztof Choromanski; Jared Quincy Davis; Valerii Likhosherstov; Xingyou Song; Jean-Jacques E. Slotine; Jacob Varley; Honglak Lee; Adrian Weller; Vikas Sindhwani (CoRR, 2020)

Understanding and Diagnosing Vulnerability under Adversarial Attacks. - Haizhong Zheng; Ziqi Zhang 004; Honglak Lee; Atul Prakash 001 (CoRR, 2020)

i-Mix: A Strategy for Regularizing Contrastive Representation Learning. - Kibok Lee 003; Yian Zhu; Kihyuk Sohn; Chun-Liang Li; Jinwoo Shin; Honglak Lee (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)

What's in a Loss Function for Image Classification? - Simon Kornblith; Honglak Lee; Ting Chen 007; Mohammad Norouzi 002 (CoRR, 2020)

Few-shot Sequence Learning with Transformers. - Lajanugen Logeswaran; Ann Lee 001; Myle Ott; Honglak Lee; Marc'Aurelio Ranzato; Arthur Szlam (CoRR, 2020)

Improved Consistency Regularization for GANs. - Zhengli Zhao; Sameer Singh 001; Honglak Lee; Zizhao Zhang; Augustus Odena; Han Zhang 010 (AAAI, 2021)

Cross-Modal Contrastive Learning for Text-to-Image Generation. - Han Zhang 010; Jing Yu Koh; Jason Baldridge; Honglak Lee; Yinfei Yang (CVPR, 2021)

Pathdreamer: A World Model for Indoor Navigation. - Jing Yu Koh; Honglak Lee; Yinfei Yang; Jason Baldridge; Peter Anderson (ICCV, 2021)

Evolving Reinforcement Learning Algorithms. - John D. Co-Reyes; Yingjie Miao; Daiyi Peng; Esteban Real; Quoc V. Le; Sergey Levine; Honglak Lee; Aleksandra Faust (ICLR, 2021)

Batch Reinforcement Learning Through Continuation Method. - Yijie Guo; Shengyu Feng; Nicolas Le Roux; Ed H. Chi; Honglak Lee; Minmin Chen (ICLR, 2021)

Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction. - Wonkwang Lee; Whie Jung; Han Zhang 010; Ting Chen 001; Jing Yu Koh; Thomas E. Huang; Hyungsuk Yoon; Honglak Lee; Seunghoon Hong (ICLR, 2021)

i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning. - Kibok Lee 003; Yian Zhu; Kihyuk Sohn; Chun-Liang Li; Jinwoo Shin; Honglak Lee (ICLR, 2021)

Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning. - Jongwook Choi; Archit Sharma; Honglak Lee; Sergey Levine; Shixiang Shane Gu (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)

Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks. - Sungryull Sohn; Sungtae Lee; Jongwook Choi; Harm van Seijen; Mehdi Fatemi; Honglak Lee (ICML, 2021)

Learning to Weight Imperfect Demonstrations. - Yunke Wang; Chang Xu 002; Bo Du 001; Honglak Lee (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)

Text as Neural Operator: Image Manipulation by Text Instruction. - Tianhao Zhang; Hung-Yu Tseng; Lu Jiang 004; Weilong Yang; Honglak Lee; Irfan Essa (ACM Multimedia, 2021)

Environment Generation for Zero-Shot Compositional Reinforcement Learning. - Izzeddin Gur; Natasha Jaques; Yingjie Miao; Jongwook Choi; Manoj Tiwari; Honglak Lee; Aleksandra Faust (NeurIPS, 2021)

Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning. - Christopher Hoang; Sungryull Sohn; Jongwook Choi; Wilka Carvalho; Honglak Lee (NeurIPS, 2021)

Why Do Better Loss Functions Lead to Less Transferable Features? - Simon Kornblith; Ting Chen 007; Honglak Lee; Mohammad Norouzi 002 (NeurIPS, 2021)

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

Text-to-Image Generation Grounded by Fine-Grained User Attention. - Jing Yu Koh; Jason Baldridge; Honglak Lee; Yinfei Yang (WACV, 2021)

Adversarial Environment Generation for Learning to Navigate the Web. - Izzeddin Gur; Natasha Jaques; Kevin Malta; Manoj Tiwari; Honglak Lee; Aleksandra Faust (CoRR, 2021)

Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning. - Jongwook Choi; Archit Sharma; Honglak Lee; Sergey Levine; Shixiang Shane Gu (CoRR, 2021)

Contrastive Representation Learning for Rapid Intraoperative Diagnosis of Skull Base Tumors Imaged Using Stimulated Raman Histology. - Cheng Jiang 003; Abhishek Bhattacharya; Joseph Linzey; Rushikesh S. Joshi; Sung Jik Cha; Sudharsan Srinivasan; Daniel Alber; Akhil Kondepudi; Esteban Urias; Balaji Pandian; Wajd Al-Holou; Steve Sullivan; et al. (CoRR, 2021)

Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks. - Yijie Guo; Qiucheng Wu; Honglak Lee (AAAI, 2022)

Learning Parameterized Task Structure for Generalization to Unseen Entities. - Anthony Z. Liu; Sungryull Sohn; Mahdi Qazwini; Honglak Lee (AAAI, 2022)

Context aware Named Entity Recognition and Relation Extraction with Domain-specific language model. - Youngrok Jang; Hosung Song; Junho Lee; Gyeonghun Kim; Yireun Kim; Stanley Jungkyu Choi; Honglak Lee; Kyunghoon Bae (CLEF (Working Notes), 2022)

Extended Overview of ChEMU 2022 Evaluation Campaign: Information Extraction in Chemical Patents. - Yuan Li 012; Biaoyan Fang; Jiayuan He 002; Hiyori Yoshikawa; Saber A. Akhondi; Christian Druckenbrodt; Camilo Thorne; Zubair Afzal; Zenan Zhai; Kojiro Machi; Masaharu Yoshioka; Youngrok Jang; et al. (CLEF (Working Notes), 2022)

L-Verse: Bidirectional Generation Between Image and Text. - Taehoon Kim; Gwangmo Song; Sihaeng Lee; Sangyun Kim; Yewon Seo; Soonyoung Lee; Seung Hwan Kim; Honglak Lee; Kyunghoon Bae (CVPR, 2022)

Lipschitz-constrained Unsupervised Skill Discovery. - Seohong Park; Jongwook Choi; Jaekyeom Kim; Honglak Lee; Gunhee Kim (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)

Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules. - Juhwan Noh; Dae-Woong Jeong; Kiyoung Kim; Sehui Han; Moontae Lee; Honglak Lee; Yousung Jung (ICML, 2022)

Fully Convolutional Transformer with Local-Global Attention. - Sihaeng Lee; Eojindl Yi; Janghyeon Lee 001; Jinsu Yoo; Honglak Lee; Seung Hwan Kim (IROS, 2022)

Few-shot Subgoal Planning with Language Models. - Lajanugen Logeswaran; Yao Fu; Moontae Lee; Honglak Lee (NAACL-HLT, 2022)

OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology. - Cheng Jiang 003; Asadur Chowdury; Xinhai Hou; Akhil Kondepudi; Christian W. Freudiger; Kyle Conway; Sandra Camelo-Piragua; Daniel A. Orringer; Honglak Lee; Todd C. Hollon (NeurIPS, 2022)

Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. - Sungjun Cho; Seonwoo Min; Jinwoo Kim; Moontae Lee; Honglak Lee; Seunghoon Hong (NeurIPS, 2022)

CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition. - Rodrigo Hormazabal; Changyoung Park; Soonyoung Lee; Sehui Han; Yeonsik Jo; Jaewan Lee; Ahra Jo; Seung Hwan Kim; Jaegul Choo; Moontae Lee; Honglak Lee (NeurIPS, 2022)

Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. - Byoungjip Kim; Sungik Choi; Dasol Hwang; Moontae Lee; Honglak Lee (NeurIPS, 2022)

Pure Transformers are Powerful Graph Learners. - Jinwoo Kim; Dat Nguyen; Seonwoo Min; Sungjun Cho; Moontae Lee; Honglak Lee; Seunghoon Hong (NeurIPS, 2022)

UniCLIP: Unified Framework for Contrastive Language-Image Pre-training. - Janghyeon Lee 001; Jongsuk Kim; Hyounguk Shon; Bumsoo Kim; Seung Hwan Kim; Honglak Lee; Junmo Kim 002 (NeurIPS, 2022)

Fast inference and transfer of compositional task structures for few-shot task generalization. - Sungryull Sohn; Hyunjae Woo; Jongwook Choi; Lyubing Qiang; Izzeddin Gur; Aleksandra Faust; Honglak Lee (UAI, 2022)

Rich CNN-Transformer Feature Aggregation Networks for Super-Resolution. - Jinsu Yoo; Taehoon Kim; Sihaeng Lee; Seung Hwan Kim; Honglak Lee; Tae Hyun Kim 006 (CoRR, 2022)

RiCS: A 2D Self-Occlusion Map for Harmonizing Volumetric Objects. - Yunseok Jang 001; Ruben Villegas; Jimei Yang; Duygu Ceylan; Xin Sun 014; Honglak Lee (CoRR, 2022)

LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA. - Muhammad Khalifa; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Lu Wang 008 (CoRR, 2022)

Is Continual Learning Truly Learning Representations Continually? - Sungmin Cha; Dongsub Shim; Hyunwoo Kim; Moontae Lee; Honglak Lee; Taesup Moon (CoRR, 2022)

Pure Transformers are Powerful Graph Learners. - Jinwoo Kim; Tien Dat Nguyen; Seonwoo Min; Sungjun Cho; Moontae Lee; Honglak Lee; Seunghoon Hong (CoRR, 2022)

Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders. - Jongseong Jang; Daeun Kyung; Seung Hwan Kim; Honglak Lee; Kyunghoon Bae; Edward Choi (CoRR, 2022)

Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters. - Sung Moon Ko; Sungjun Cho; Dae-Woong Jeong; Sehui Han; Moontae Lee; Honglak Lee (AAAI, 2023)

Simple and Effective Synthesis of Indoor 3D Scenes. - Jing Yu Koh; Harsh Agrawal; Dhruv Batra; Richard Tucker; Austin Waters; Honglak Lee; Yinfei Yang; Jason Baldridge; Peter Anderson (AAAI, 2023)

Learning Compositional Tasks from Language Instructions. - Lajanugen Logeswaran; Wilka Carvalho; Honglak Lee (AAAI, 2023)

Few-shot Reranking for Multi-hop QA via Language Model Prompting. - Muhammad Khalifa; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Lu Wang 008 (ACL (1), 2023)

Unsupervised Task Graph Generation from Instructional Video Transcripts. - Lajanugen Logeswaran; Sungryull Sohn; Yunseok Jang 001; Moontae Lee; Honglak Lee (ACL (Findings), 2023)

Hierarchical Discriminative Learning Improves Visual Representations of Biomedical Microscopy. - Cheng Jiang 003; Xinhai Hou; Akhil Kondepudi; Asadur Chowdury; Christian W. Freudiger; Daniel A. Orringer; Honglak Lee; Todd C. Hollon (CVPR, 2023)

GRACE: Discriminator-Guided Chain-of-Thought Reasoning. - Muhammad Khalifa; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Lu Wang 008 (EMNLP (Findings), 2023)

A Picture is Worth a Thousand Words: Language Models Plan from Pixels. - Anthony Z. Liu; Lajanugen Logeswaran; Sungryull Sohn; Honglak Lee (EMNLP, 2023)

TOD-Flow: Modeling the Structure of Task-Oriented Dialogues. - Sungryull Sohn; Yiwei Lyu; Anthony Z. Liu; Lajanugen Logeswaran; Dong-Ki Kim; Dongsub Shim; Honglak Lee (EMNLP, 2023)

Merging Generated and Retrieved Knowledge for Open-Domain QA. - Yunxiang Zhang; Muhammad Khalifa; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Lu Wang 008 (EMNLP, 2023)

From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning. - Zheyuan Zhang; Shane Storks; Fengyuan Hu; Sungryull Sohn; Moontae Lee; Honglak Lee; Joyce Chai (EMNLP, 2023)

Lightweight Feature Encoder for Wake-Up Word Detection Based on Self-Supervised Speech Representation. - Hyungjun Lim; Younggwan Kim; Kiho Yeom; Eunjoo Seo; Hoodong Lee; Stanley Jungkyu Choi; Honglak Lee (ICASSP, 2023)

Story Visualization by Online Text Augmentation with Context Memory. - Daechul Ahn; Daneul Kim; Gwangmo Song; Seung Hwan Kim; Honglak Lee; Dongyeop Kang; Jonghyun Choi (ICCV, 2023)

Composing Task Knowledge With Modular Successor Feature Approximators. - Wilka Carvalho; Angelos Filos; Richard L. Lewis; Honglak Lee; Satinder Singh 001 (ICLR, 2023)

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

Go Beyond Imagination: Maximizing Episodic Reachability with World Models. - Yao Fu; Run Peng; Honglak Lee (ICML, 2023)

Investigation of Training Mute-Expressive End-to-End Speech Separation Networks for an Unknown Number of Speakers. - Younggwan Kim; Hyungjun Lim; Kiho Yeom; Eunjoo Seo; Hoodong Lee; Stanley Jungkyu Choi; Honglak Lee (INTERSPEECH, 2023)

Combining Behaviors with the Successor Features Keyboard. - Wilka Carvalho; Andre Saraiva 001; Angelos Filos; Andrew K. Lampinen; Loic Matthey; Richard L. Lewis; Honglak Lee; Satinder Singh 001; Danilo Jimenez Rezende; Daniel Zoran (NeurIPS, 2023)

Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models. - Sungik Choi; Hankook Lee; Honglak Lee; Moontae Lee (NeurIPS, 2023)

SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations. - Youngsoo Jang; Geon-Hyeong Kim; Jongmin Lee 004; Sungryull Sohn; Byoungjip Kim; Honglak Lee; Moontae 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)

Scalable 3D Captioning with Pretrained Models. - Tiange Luo; Chris Rockwell 001; Honglak Lee; Justin Johnson 001 (NeurIPS, 2023)

CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation. - Sihan Xu; Ziqiao Ma 001; Yidong Huang; Honglak Lee; Joyce Chai (NeurIPS, 2023)

Fine-grained Text Style Transfer with Diffusion-Based Language Models. - Yiwei Lyu; Tiange Luo; Jiacheng Shi; Todd C. Hollon; Honglak Lee (RepL4NLP@ACL, 2023)

Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution. - Jinsu Yoo; Taehoon Kim; Sihaeng Lee; Seung Hwan Kim; Honglak Lee; Tae Hyun Kim 006 (WACV, 2023)

Multimodal Subtask Graph Generation from Instructional Videos. - Yunseok Jang 001; Sungryull Sohn; Lajanugen Logeswaran; Tiange Luo; Moontae Lee; Honglak Lee (CoRR, 2023)

Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging. - Todd C. Hollon; Cheng Jiang 003; Asadur Chowdury; Mustafa Nasir-Moin; Akhil Kondepudi; Alexander Aabedi; Arjun Adapa; Wajd Al-Holou; Jason Heth; Oren Sagher; Pedro R. Lowenstein; Maria Castro; et al. (CoRR, 2023)

Discriminator-Guided Multi-step Reasoning with Language Models. - Muhammad Khalifa; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Lu Wang 008 (CoRR, 2023)

Exploring Demonstration Ensembling for In-context Learning. - Muhammad Khalifa; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Lu Wang 008 (CoRR, 2023)

Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning. - Sungjun Cho; Seunghyuk Cho; Sungwoo Park; Hankook Lee; Honglak Lee; Moontae Lee (CoRR, 2023)

MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning. - Dong-Ki Kim; Sungryull Sohn; Lajanugen Logeswaran; Dongsub Shim; Honglak Lee (CoRR, 2023)

Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program. - Tiange Luo; Honglak Lee; Justin Johnson 001 (Trans. Mach. Learn. Res., 2023)

Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. - Sungmin Cha; Sungjun Cho; Dasol Hwang; Honglak Lee; Taesup Moon; Moontae Lee (AAAI, 2024)

Unsupervised Object Interaction Learning with Counterfactual Dynamics Models. - Jongwook Choi; Sungtae Lee; Xinyu Wang; Sungryull Sohn; Honglak Lee (AAAI, 2024)

Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning. - Janghoon Han; Changho Lee; Joongbo Shin; Stanley Jungkyu Choi; Honglak Lee; Kyunghoon Bae (ACL (Findings), 2024)

Mitigating Biases for Instruction-following Language Models via Bias Neurons Elimination. - Nakyeong Yang; Taegwan Kang; Stanley Jungkyu Choi; Honglak Lee; Kyomin Jung (ACL (1), 2024)

Small Language Models Need Strong Verifiers to Self-Correct Reasoning. - Yunxiang Zhang; Muhammad Khalifa; Lajanugen Logeswaran; Jaekyeom Kim; Moontae Lee; Honglak Lee; Lu Wang 008 (ACL (Findings), 2024)

Towards More Diverse Evaluation of Class Incremental Learning: Representation Learning Perspective. - Sungmin Cha; Jihwan Kwak; Dongsub Shim; Hyunwoo Kim; Moontae Lee; Honglak Lee; Taesup Moon (CoLLAs, 2024)

Super-resolution of biomedical volumes with 2D supervision. - Cheng Jiang 003; Alexander Gedeon; Yiwei Lyu; Eric Landgraf; Yufeng Zhang; Xinhai Hou; Akhil Kondepudi; Asadur Chowdury; Honglak Lee; Todd C. Hollon (CVPR Workshops, 2024)

NICE: CVPR 2023 Challenge on Zero-shot Image Captioning. - Taehoon Kim; Pyunghwan Ahn; Sangyun Kim; Sihaeng Lee; Mark Marsden; Alessandra Sala; Seung Hwan Kim; Bohyung Han; Kyoung Mu Lee; Honglak Lee; Kyounghoon Bae; Xiangyu Wu; et al. (CVPR Workshops, 2024)

Show, Think, and Tell: Thought-Augmented Fine-Tuning of Large Language Models for Video Captioning. - Byoungjip Kim; Dasol Hwang; Sungjun Cho; Youngsoo Jang; Honglak Lee; Moontae Lee (CVPR Workshops, 2024)

View Selection for 3D Captioning via Diffusion Ranking. - Tiange Luo; Justin Johnson 001; Honglak Lee (ECCV (31), 2024)

Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking. - Byoungjip Kim; Youngsoo Jang; Lajanugen Logeswaran; Geon-Hyeong Kim; Yu Jin Kim; Honglak Lee; Moontae Lee (EMNLP (Findings), 2024)

Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents. - Jaekyeom Kim; Dong-Ki Kim; Lajanugen Logeswaran; Sungryull Sohn; Honglak Lee (EMNLP (Findings), 2024)

Instruction Matters: A Simple yet Effective Task Selection for Optimized Instruction Tuning of Specific Tasks. - Changho Lee; Janghoon Han; Seonghyeon Ye; Stanley Jungkyu Choi; Honglak Lee; Kyunghoon Bae (EMNLP, 2024)

Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration. - Youngsoo Jang; Geon-Hyeong Kim; Byoungjip Kim; Yu Jin Kim; Honglak Lee; Moontae Lee (ICML, 2024)

Code Models are Zero-shot Precondition Reasoners. - Lajanugen Logeswaran; Sungryull Sohn; Yiwei Lyu; Anthony Z. Liu; Dong-Ki Kim; Dongsub Shim; Moontae Lee; Honglak Lee (NAACL-HLT, 2024)

Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense. - Siqi Shen; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Soujanya Poria; Rada Mihalcea (NAACL-HLT, 2024)

AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents. - Yao Fu; Dong-Ki Kim; Jaekyeom Kim; Sungryull Sohn; Lajanugen Logeswaran; Kyunghoon Bae; Honglak Lee (NeurIPS, 2024)

A self-supervised framework for learning whole slide representations. - Xinhai Hou; Cheng Jiang 003; Akhil Kondepudi; Yiwei Lyu; Asadur Zaman Chowdury; Honglak Lee; Todd C. Hollon (CoRR, 2024)

AutoGuide: Automated Generation and Selection of State-Aware Guidelines for Large Language Model Agents. - Yao Fu; Dong-Ki Kim; Jaekyeom Kim; Sungryull Sohn; Lajanugen Logeswaran; Kyunghoon Bae; Honglak Lee (CoRR, 2024)

Source-Aware Training Enables Knowledge Attribution in Language Models. - Muhammad Khalifa; David Wadden; Emma Strubell; Honglak Lee; Lu Wang 008; Iz Beltagy; Hao Peng 009 (CoRR, 2024)

Instruction Matters, a Simple yet Effective Task Selection Approach in Instruction Tuning for Specific Tasks. - Changho Lee; Janghoon Han; Seonghyeon Ye; Stanley Jungkyu Choi; Honglak Lee; Kyunghoon Bae (CoRR, 2024)

EXAONE 3.0 7.8B Instruction Tuned Language Model. - Soyoung An; Kyunghoon Bae; Eunbi Choi; Stanley Jungkyu Choi; Yemuk Choi; Seokhee Hong; Yeonjung Hong; Junwon Hwang; Hyojin Jeon; Gerrard Jeongwon Jo; Hyunjik Jo; Jiyeon Jung; et al. (CoRR, 2024)

If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs. - Muhammad Khalifa; Yi Chern Tan; Arash Ahmadian; Tom Hosking; Honglak Lee; Lu Wang 008; Ahmet Üstün; Tom Sherborne; Matthias Gallé (CoRR, 2024)

EXAONE 3.5: Series of Large Language Models for Real-world Use Cases. - LG AI Research; Soyoung An; Kyunghoon Bae; Eunbi Choi; Kibong Choi; Stanley Jungkyu Choi; Seokhee Hong; Junwon Hwang; Hyojin Jeon; Gerrard Jeongwon Jo; Hyunjik Jo; Jiyeon Jung; et al. (CoRR, 2024)

Map2Text: New Content Generation from Low-Dimensional Visualizations. - Xingjian Zhang 002; Ziyang Xiong; Shixuan Liu; Yutong Xie 007; Tolga Ergen; Dongsub Shim; Hua Xu 001; Honglak Lee; Qiaozhu Mei (CoRR, 2024)

3D Denoisers Are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation. - Sungjun Cho; Dae-Woong Jeong; Sung Moon Ko; Jinwoo Kim; Sehui Han; Seunghoon Hong; Honglak Lee; Moontae Lee (AAAI, 2025)

Step-Calibrated Diffusion for Biomedical Optical Image Restoration. - Yiwei Lyu; Sung Jik Cha; Cheng Jiang 003; Asadur Zaman Chowdury; Xinhai Hou; Edward S. Harake; Akhil Kondepudi; Christian W. Freudiger; Honglak Lee; Todd C. Hollon (AAAI, 2025)

Interactive and Expressive Code-Augmented Planning with Large Language Models. - Anthony Zhe Liu; Xinhe Wang 001; Jacob Sansom; Yao Fu; Jongwook Choi; Sungryull Sohn; Jaekyeom Kim; Honglak Lee (ACL (1), 2025)

Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents. - Yunseok Jang 001; Yeda Song; Sungryull Sohn; Lajanugen Logeswaran; Tiange Luo; Dong-Ki Kim; Kyunghoon Bae; Honglak Lee (CVPR, 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)

Hierarchical Decomposition Framework for Steiner Tree Packing Problem. - Hanbum Ko; Minu Kim; Han-Seul Jeong; Sunghoon Hong; Deunsol Yoon; Youngjoon Park; Woohyung Lim; Honglak Lee; Moontae Lee; Kanghoon Lee; Sungbin Lim; Sungryull Sohn (ICORES, 2025)

MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows. - Xingjian Zhang 002; Yutong Xie 007; Jin Huang; Jinge Ma; Zhaoying Pan; Qijia Liu; Ziyang Xiong; Tolga Ergen; Dongsub Shim; Honglak Lee; Qiaozhu Mei (NAACL (Findings), 2025)

Probing Visual Language Priors in VLMs. - Tiange Luo; Ang Cao; Gunhee Lee; Justin Johnson 001; Honglak Lee (CoRR, 2025)

Clear Preferences Leave Traces: Reference Model-Guided Sampling for Preference Learning. - Nirav Diwan; Tolga Ergen; Dongsub Shim; Honglak Lee (CoRR, 2025)

Foundation models for fast, label-free detection of glioma infiltration. - Akhil Kondepudi; Melike Pekmezci; Xinhai Hou; Katie Scotford; Cheng Jiang 003; Akshay Rao; Edward S. Harake; Asadur Chowdury; Wajd Al-Holou; Lin Wang; Aditya Pandey; Pedro R. Lowenstein; et al. (Nat., 2025)

KL Penalty Control via Perturbation for Direct Preference Optimization. - Sangkyu Lee; Janghoon Han; Hosung Song; Stanley Jungkyu Choi; Honglak Lee; Youngjae Yu (CoRR, 2025)

Do Not Trust Licenses You See: Dataset Compliance Requires Massive-Scale AI-Powered Lifecycle Tracing. - Jaekyeom Kim; Sungryull Sohn; Gerrard Jeongwon Jo; Jihoon Choi; Kyunghoon Bae; Hwayoung Lee; Yongmin Park; Honglak Lee (CoRR, 2025)

EXAONE Deep: Reasoning Enhanced Language Models. - LG AI Research; Kyunghoon Bae; Eunbi Choi; Kibong Choi; Stanley Jungkyu Choi; Yemuk Choi; Seokhee Hong; Junwon Hwang; Hyojin Jeon; Kijeong Jeon; Gerrard Jeongwon Jo; Hyunjik Jo; et al. (CoRR, 2025)

MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges? - Yunxiang Zhang; Muhammad Khalifa; Shitanshu Bhushan; Grant D. Murphy; Lajanugen Logeswaran; Jaekyeom Kim; Moontae Lee; Honglak Lee; Lu Wang 008 (CoRR, 2025)

Process Reward Models That Think. - Muhammad Khalifa; Rishabh Agarwal; Lajanugen Logeswaran; Jaekyeom Kim; Hao Peng 009; Moontae Lee; Honglak Lee; Lu Wang 008 (CoRR, 2025)

Visual Test-time Scaling for GUI Agent Grounding. - Tiange Luo; Lajanugen Logeswaran; Justin Johnson 001; Honglak Lee (CoRR, 2025)

SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety. - Geon-Hyeong Kim; Youngsoo Jang; Yu Jin Kim; Byoungjip Kim; Honglak Lee; Kyunghoon Bae; Moontae Lee (CoRR, 2025)

Towards Scalable Language-Image Pre-training for 3D Medical Imaging. - Chenhui Zhao; Yiwei Lyu; Asadur Chowdury; Edward S. Harake; Akhil Kondepudi; Akshay Rao; Xinhai Hou; Honglak Lee; Todd C. Hollon (CoRR, 2025)

Active Test-time Vision-Language Navigation. - Heeju Ko; Sungjune Kim; Gyeongrok Oh; Jeongyoon Yoon; Honglak Lee; Sujin Jang; Seungryong Kim; Sangpil Kim (CoRR, 2025)

LGAI-EMBEDDING-Preview Technical Report. - Jooyoung Choi; Hyun Kim; Hansol Jang; Changwook Jun; Kyunghoon Bae; Hyewon Choi; Stanley Jungkyu Choi; Honglak Lee; Chulmin Yun (CoRR, 2025)

Preemptive Solving of Future Problems: Multitask Preplay in Humans and Machines. - Wilka Carvalho; Sam Hall-McMaster; Honglak Lee; Samuel J. Gershman (CoRR, 2025)

EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes. - Kyunghoon Bae; Eunbi Choi; Kibong Choi; Stanley Jungkyu Choi; Yemuk Choi; Kyubeen Han; Seokhee Hong; Junwon Hwang; Taewan Hwang; Joonwon Jang; Hyojin Jeon; Kijeong Jeon; et al. (CoRR, 2025)

Revisiting LLM Value Probing Strategies: Are They Robust and Expressive? - Siqi Shen; Mehar Singh; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Rada Mihalcea (CoRR, 2025)