Honglak Lee

391 papers A* 122A 12C 2Misc 2Journal 191Unranked 60
YearRankTypeTitle / Venue / Authors
2026 — conf
Beyond Blind Following: Evaluating Robustness of LLM Agents under Imperfect Guidance.
EACL (Volume 1: Long Papers)
Yao Fu, Ran Qiu, Xinhe Wang, Jacob Sansom, Sathvika Ayyappa Prabhu, Huijie Tang, Jaekyeom Kim, Sungryull Sohn, Honglak Lee
2026 J jnl
Gaming the Judge: Unfaithful Chain-of-Thought Can Undermine Agent Evaluation.
CoRR
Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Sungryull Sohn, Yunxiang Zhang, Moontae Lee, Hao Peng, Lu Wang, Honglak Lee
2026 — conf
IRPO: Implicit Policy Regularized Preference Optimization.
EACL (Findings)
Youngsoo Jang, Yu Jin Kim, Geon-Hyeong Kim, Honglak Lee, Moontae Lee
2026 J jnl
K-EXAONE Technical Report.
CoRR
LG AI Research, Yejin Choi, Jiwon Ham, Kijeong Jeon, Gerrard Jeongwon Jo, Yonghwan Jo, Jiyeon Jung, Naeun Kang, Dohoon Kim, Euisoon Kim, Hayeon Kim, Hyosang Kim, Hyunseo Kim, Jieun Kim, Minu Kim, Myoungshin Kim, Unsol Kim, Youchul Kim, Youngjin Kim, Chaeeun Lee, Chaeyoon Lee, Changhun Lee, Dahm Lee, Edward Hwayoung Lee, Honglak Lee, Jinsang Lee
2026 J jnl
Process Reward Models That Think.
Trans. Mach. Learn. Res.
Muhammad Khalifa, Rishabh Agarwal, Lajanugen Logeswaran, Jaekyeom Kim, Hao Peng, Moontae Lee, Honglak Lee, Lu Wang
2026 J jnl
Scaling Web Agent Training through Automatic Data Generation and Fine-grained Evaluation.
CoRR
Lajanugen Logeswaran, Jaekyeom Kim, Sungryull Sohn, Creighton Glasscock, Honglak Lee
2026 J jnl
Towards Scalable Language-Image Pre-training for 3D Medical Imaging.
Trans. Mach. Learn. Res.
Chenhui Zhao, Yiwei Lyu, Asadur Zaman Chowdury, Edward S. Harake, Akhil Kondepudi, Akshay Rao, Xinhai Hou, Honglak Lee, Todd C. Hollon
2025 A* conf
3D Denoisers Are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation.
AAAI
Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko, Jinwoo Kim, Sehui Han, Seunghoon Hong, Honglak Lee, Moontae Lee
2025 J jnl
A Definition of AGI.
CoRR
Dan Hendrycks, Dawn Song, Christian Szegedy, Honglak Lee, Yarin Gal, Erik Brynjolfsson, Sharon Li, Andy Zou, Lionel Levine, Bo Han, Jie Fu, Ziwei Liu, Jinwoo Shin, Kimin Lee, Mantas Mazeika, Long Phan, George Ingebretsen, Adam Khoja, Cihang Xie, Olawale Salaudeen, Matthias Hein, Kevin Zhao, Alexander Pan, David Duvenaud, Bo Li, Steve Omohundro, Gabriel Alfour, Max Tegmark, Kevin McGrew, Gary Marcus, Jaan Tallinn, Eric Schmidt, Yoshua Bengio
2025 J jnl
Active Test-time Vision-Language Navigation.
CoRR
Heeju Ko, Sungjune Kim, Gyeongrok Oh, Jeongyoon Yoon, Honglak Lee, Sujin Jang, Seungryong Kim, Sangpil Kim
2025 J jnl
Clear Preferences Leave Traces: Reference Model-Guided Sampling for Preference Learning.
CoRR
Nirav Diwan, Tolga Ergen, Dongsub Shim, Honglak Lee
2025 J jnl
DEER: A Comprehensive and Reliable Benchmark for Deep-Research Expert Reports.
CoRR
Janghoon Han, Heegyu Kim, Changho Lee, Dahm Lee, Min Hyung Park, Hosung Song, Stanley Jungkyu Choi, Moontae Lee, Honglak Lee
2025 J jnl
Do Not Trust Licenses You See: Dataset Compliance Requires Massive-Scale AI-Powered Lifecycle Tracing.
CoRR
Jaekyeom Kim, Sungryull Sohn, Gerrard Jeongwon Jo, Jihoon Choi, Kyunghoon Bae, Hwayoung Lee, Yongmin Park, Honglak Lee
2025 J jnl
EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes.
CoRR
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, Gerrard Jeongwon Jo, Hyunjik Jo, Jiyeon Jung, Euisoon Kim, Hyosang Kim, Jihoon Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Yongil Kim, Youchul Kim, Edward Hwayoung Lee, Gwangho Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lee, Sangha Park, Young Min Paik, Yongmin Park, Youngyong Park, Sanghyun Seo, Sihoon Yang, Heuiyeen Yeen, Sihyuk Yi, Hyeongu Yun
2025 J jnl
EXAONE Deep: Reasoning Enhanced Language Models.
CoRR
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, Jiyeon Jung, Hyosang Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Yongil Kim, Youchul Kim, Edward Hwayoung Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lee, Sangha Park, Yongmin Park, Sihoon Yang, Heuiyeen Yeen, Sihyuk Yi, Hyeongu Yun
2025 J jnl
Foundation models for fast, label-free detection of glioma infiltration.
Nat.
Akhil Kondepudi, Melike Pekmezci, Xinhai Hou, Katie Scotford, Cheng Jiang, Akshay Rao, Edward S. Harake, Asadur Chowdury, Wajd N. Al-Holou, Lin Wang, Aditya Pandey, Pedro R. Lowenstein, Maria G. Castro, Lisa Irina Koerner, Thomas Roetzer-Pejrimovsky, Georg Widhalm, Sandra Camelo-Piragua, Misha Movahed-Ezazi, Daniel A. Orringer, Honglak Lee, Christian W. Freudiger, Mitchel S. Berger, Shawn Hervey-Jumper, Todd C. Hollon
2025 J jnl
Health system learning achieves generalist neuroimaging models.
CoRR
Akhil Kondepudi, Akshay Rao, Chenhui Zhao, Yiwei Lyu, Edward S. Harake, Soumyanil Banerjee, Rushikesh S. Joshi, Anna-Katharina Meißner, Renly Hou, Cheng Jiang, Asadur Chowdury, Ashok Srinivasan, Brian Athey, Vikas Gulani, Aditya Pandey, Honglak Lee, Todd C. Hollon
2025 C conf
Hierarchical Decomposition Framework for Steiner Tree Packing Problem.
ICORES
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
2025 — conf
Interactive and Expressive Code-Augmented Planning with Large Language Models.
ACL (1)
Anthony Zhe Liu, Xinhe Wang, Jacob Sansom, Yao Fu, Jongwook Choi, Sungryull Sohn, Jaekyeom Kim, Honglak Lee
2025 J jnl
KL Penalty Control via Perturbation for Direct Preference Optimization.
CoRR
Sangkyu Lee, Janghoon Han, Hosung Song, Stanley Jungkyu Choi, Honglak Lee, Youngjae Yu
2025 J jnl
LGAI-EMBEDDING-Preview Technical Report.
CoRR
Jooyoung Choi, Hyun Kim, Hansol Jang, Changwook Jun, Kyunghoon Bae, Hyewon Choi, Stanley Jungkyu Choi, Honglak Lee, Chulmin Yun
2025 J jnl
Learning complete and explainable visual representations from itemized text supervision.
CoRR
Yiwei Lyu, Chenhui Zhao, Soumyanil Banerjee, Shixuan Liu, Akshay Rao, Akhil Kondepudi, Honglak Lee, Todd C. Hollon
2025 J jnl
Learning neuroimaging models from health system-scale data.
CoRR
Yiwei Lyu, Edward S. Harake, Asadur Chowdury, Soumyanil Banerjee, Rachel Gologorsky, Shixuan Liu, Anna-Katharina Meißner, Akshay Rao, Chenhui Zhao, Akhil Kondepudi, Cheng Jiang, Xinhai Hou, Rushikesh S. Joshi, Volker Neuschmelting, Ashok Srinivasan, Dawn Kleindorfer, Brian Athey, Vikas Gulani, Aditya Pandey, Honglak Lee, Todd C. Hollon
2025 — conf
MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows.
NAACL (Findings)
Xingjian Zhang, Yutong Xie, Jin Huang, Jinge Ma, Zhaoying Pan, Qijia Liu, Ziyang Xiong, Tolga Ergen, Dongsub Shim, Honglak Lee, Qiaozhu Mei
2025 J jnl
MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges?
CoRR
Yunxiang Zhang, Muhammad Khalifa, Shitanshu Bhushan, Grant D. Murphy, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
2025 — conf
MapExplorer: New Content Generation from Low-Dimensional Visualizations.
KDD (2)
Xingjian Zhang, Ziyang Xiong, Shixuan Liu, Yutong Xie, Tolga Ergen, Dongsub Shim, Hua Xu, Honglak Lee, Qiaozhu Mei
2025 J jnl
Preemptive Solving of Future Problems: Multitask Preplay in Humans and Machines.
CoRR
Wilka Carvalho, Sam Hall-McMaster, Honglak Lee, Samuel J. Gershman
2025 A* conf
Probing Visual Language Priors in VLMs.
ICML
Tiange Luo, Ang Cao, Gunhee Lee, Justin Johnson, Honglak Lee
2025 J jnl
Probing Visual Language Priors in VLMs.
CoRR
Tiange Luo, Ang Cao, Gunhee Lee, Justin Johnson, Honglak Lee
2025 J jnl
Process Reward Models That Think.
CoRR
Muhammad Khalifa, Rishabh Agarwal, Lajanugen Logeswaran, Jaekyeom Kim, Hao Peng, Moontae Lee, Honglak Lee, Lu Wang
2025 A* conf
Revisiting LLM Value Probing Strategies: Are They Robust and Expressive?
EMNLP
Siqi Shen, Mehar Singh, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Rada Mihalcea
2025 J jnl
Revisiting LLM Value Probing Strategies: Are They Robust and Expressive?
CoRR
Siqi Shen, Mehar Singh, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Rada Mihalcea
2025 J jnl
SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety.
CoRR
Geon-Hyeong Kim, Youngsoo Jang, Yu Jin Kim, Byoungjip Kim, Honglak Lee, Kyunghoon Bae, Moontae Lee
2025 A* conf
Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents.
CVPR
Yunseok Jang, Yeda Song, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Dong-Ki Kim, Kyunghoon Bae, Honglak Lee
2025 J jnl
Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents.
CoRR
Yunseok Jang, Yeda Song, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Dong-Ki Kim, Kyunghoon Bae, Honglak Lee
2025 J jnl
Spanning Tree Autoregressive Visual Generation.
CoRR
Sangkyu Lee, Changho Lee, Janghoon Han, Hosung Song, Tackgeun You, Hwasup Lim, Stanley Jungkyu Choi, Honglak Lee, Youngjae Yu
2025 A* conf
Step-Calibrated Diffusion for Biomedical Optical Image Restoration.
AAAI
Yiwei Lyu, Sung Jik Cha, Cheng Jiang, Asadur Zaman Chowdury, Xinhai Hou, Edward S. Harake, Akhil Kondepudi, Christian W. Freudiger, Honglak Lee, Todd C. Hollon
2025 A* conf
Subtask-Aware Visual Reward Learning from Segmented Demonstrations.
ICLR
Changyeon Kim, Minho Heo, Doohyun Lee, Honglak Lee, Jinwoo Shin, Joseph J. Lim, Kimin Lee
2025 J jnl
Subtask-Aware Visual Reward Learning from Segmented Demonstrations.
CoRR
Changyeon Kim, Minho Heo, Doohyun Lee, Jinwoo Shin, Honglak Lee, Joseph J. Lim, Kimin Lee
2025 J jnl
Towards Minimal Fine-Tuning of VLMs.
CoRR
Tiange Luo, Lajanugen Logeswaran, Jaekyeom Kim, Justin Johnson, Honglak Lee
2025 J jnl
Towards Scalable Language-Image Pre-training for 3D Medical Imaging.
CoRR
Chenhui Zhao, Yiwei Lyu, Asadur Chowdury, Edward S. Harake, Akhil Kondepudi, Akshay Rao, Xinhai Hou, Honglak Lee, Todd C. Hollon
2025 J jnl
Visual Test-time Scaling for GUI Agent Grounding.
CoRR
Tiange Luo, Lajanugen Logeswaran, Justin Johnson, Honglak Lee
2024 J jnl
A self-supervised framework for learning whole slide representations.
CoRR
Xinhai Hou, Cheng Jiang, Akhil Kondepudi, Yiwei Lyu, Asadur Zaman Chowdury, Honglak Lee, Todd C. Hollon
2024 — conf
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents.
EMNLP (Findings)
Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
2024 J jnl
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents.
CoRR
Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
2024 A* conf
AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents.
NeurIPS
Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee
2024 J jnl
AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents.
CoRR
Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee
2024 — conf
Code Models are Zero-shot Precondition Reasoners.
NAACL-HLT
Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu, Anthony Z. Liu, Dong-Ki Kim, Dongsub Shim, Moontae Lee, Honglak Lee
2024 — conf
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning.
ACL (Findings)
Janghoon Han, Changho Lee, Joongbo Shin, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae
2024 J jnl
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning.
CoRR
Janghoon Han, Changho Lee, Joongbo Shin, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae
2024 A* conf
Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration.
ICML
Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim, Yu Jin Kim, Honglak Lee, Moontae Lee
2024 J jnl
EXAONE 3.0 7.8B Instruction Tuned Language Model.
CoRR
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, Yountae Jung, Euisoon Kim, Hyosang Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Youchul Kim, Edward Hwayoung Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lee, Moontae Lee, Seungjun Lee, Woohyung Lim, Sangha Park, Sooyoun Park, Yongmin Park, Boseong Seo, Sihoon Yang, Heuiyeen Yeen, Kyungjae Yoo, Hyeongu Yun
2024 J jnl
EXAONE 3.5: Series of Large Language Models for Real-world Use Cases.
CoRR
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, Yountae Jung, Hyosang Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Yongil Kim, Youchul Kim, Edward Hwayoung Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lee, Woohyung Lim, Sangha Park, Sooyoun Park, Yongmin Park, Sihoon Yang, Heuiyeen Yeen, Hyeongu Yun
2024 J jnl
If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs.
CoRR
Muhammad Khalifa, Yi Chern Tan, Arash Ahmadian, Tom Hosking, Honglak Lee, Lu Wang, Ahmet Üstün, Tom Sherborne, Matthias Gallé
2024 J jnl
Instruction Matters, a Simple yet Effective Task Selection Approach in Instruction Tuning for Specific Tasks.
CoRR
Changho Lee, Janghoon Han, Seonghyeon Ye, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae
2024 A* conf
Instruction Matters: A Simple yet Effective Task Selection for Optimized Instruction Tuning of Specific Tasks.
EMNLP
Changho Lee, Janghoon Han, Seonghyeon Ye, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae
2024 J jnl
Interactive and Expressive Code-Augmented Planning with Large Language Models.
CoRR
Anthony Z. Liu, Xinhe Wang, Jacob Sansom, Yao Fu, Jongwook Choi, Sungryull Sohn, Jaekyeom Kim, Honglak Lee
2024 A* conf
Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers.
AAAI
Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
2024 J jnl
MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows.
CoRR
Xingjian Zhang, Yutong Xie, Jin Huang, Jinge Ma, Zhaoying Pan, Qijia Liu, Ziyang Xiong, Tolga Ergen, Dongsub Shim, Honglak Lee, Qiaozhu Mei
2024 J jnl
Map2Text: New Content Generation from Low-Dimensional Visualizations.
CoRR
Xingjian Zhang, Ziyang Xiong, Shixuan Liu, Yutong Xie, Tolga Ergen, Dongsub Shim, Hua Xu, Honglak Lee, Qiaozhu Mei
2024 — conf
Mitigating Biases for Instruction-following Language Models via Bias Neurons Elimination.
ACL (1)
Nakyeong Yang, Taegwan Kang, Stanley Jungkyu Choi, Honglak Lee, Kyomin Jung
2024 — conf
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning.
CVPR Workshops
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, Yi Gao, Hailiang Zhang, Yang Yang, Weili Guo, Jianfeng Lu, Youngtaek Oh, Jae-Won Cho, Dong-Jin Kim, In So Kweon, Junmo Kim, Wooyoung Kang, Won Young Jhoo, Byungseok Roh, Jonghwan Mun, Solgil Oh, Kenan Emir Ak, Gwang-Gook Lee, Yan Xu, Mingwei Shen, Kyomin Hwang, Wonsik Shin, Kamin Lee, Wonhark Park, Dongkwan Lee, Nojun Kwak, Yujin Wang, Yimu Wang, Tiancheng Gu, Xingchang Lv, Mingmao Sun
2024 — conf
Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking.
EMNLP (Findings)
Byoungjip Kim, Youngsoo Jang, Lajanugen Logeswaran, Geon-Hyeong Kim, Yu Jin Kim, Honglak Lee, Moontae Lee
2024 — conf
Show, Think, and Tell: Thought-Augmented Fine-Tuning of Large Language Models for Video Captioning.
CVPR Workshops
Byoungjip Kim, Dasol Hwang, Sungjun Cho, Youngsoo Jang, Honglak Lee, Moontae Lee
2024 — conf
Small Language Models Need Strong Verifiers to Self-Correct Reasoning.
ACL (Findings)
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
2024 J jnl
Small Language Models Need Strong Verifiers to Self-Correct Reasoning.
CoRR
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
2024 J jnl
Source-Aware Training Enables Knowledge Attribution in Language Models.
CoRR
Muhammad Khalifa, David Wadden, Emma Strubell, Honglak Lee, Lu Wang, Iz Beltagy, Hao Peng
2024 J jnl
Step-Calibrated Diffusion for Biomedical Optical Image Restoration.
CoRR
Yiwei Lyu, Sung Jik Cha, Cheng Jiang, Asadur Chowdury, Xinhai Hou, Edward S. Harake, Akhil Kondepudi, Christian W. Freudiger, Honglak Lee, Todd C. Hollon
2024 — conf
Super-resolution of biomedical volumes with 2D supervision.
CVPR Workshops
Cheng Jiang, Alexander Gedeon, Yiwei Lyu, Eric Landgraf, Yufeng Zhang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Honglak Lee, Todd C. Hollon
2024 J jnl
Super-resolution of biomedical volumes with 2D supervision.
CoRR
Cheng Jiang, Alexander Gedeon, Yiwei Lyu, Eric Landgraf, Yufeng Zhang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Honglak Lee, Todd C. Hollon
2024 — conf
Towards More Diverse Evaluation of Class Incremental Learning: Representation Learning Perspective.
CoLLAs
Sungmin Cha, Jihwan Kwak, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon
2024 — conf
Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense.
NAACL-HLT
Siqi Shen, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Soujanya Poria, Rada Mihalcea
2024 J jnl
Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense.
CoRR
Siqi Shen, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Soujanya Poria, Rada Mihalcea
2024 A* conf
Unsupervised Object Interaction Learning with Counterfactual Dynamics Models.
AAAI
Jongwook Choi, Sungtae Lee, Xinyu Wang, Sungryull Sohn, Honglak Lee
2024 — conf
View Selection for 3D Captioning via Diffusion Ranking.
ECCV (31)
Tiange Luo, Justin Johnson, Honglak Lee
2024 J jnl
View Selection for 3D Captioning via Diffusion Ranking.
CoRR
Tiange Luo, Justin Johnson, Honglak Lee
2023 J jnl
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation.
CoRR
Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko, Jinwoo Kim, Sehui Han, Seunghoon Hong, Honglak Lee, Moontae Lee
2023 A* conf
A Picture is Worth a Thousand Words: Language Models Plan from Pixels.
EMNLP
Anthony Z. Liu, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
2023 J jnl
A Picture is Worth a Thousand Words: Language Models Plan from Pixels.
CoRR
Anthony Z. Liu, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
2023 J jnl
Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging.
CoRR
Todd C. Hollon, Cheng Jiang, Asadur Chowdury, Mustafa Nasir-Moin, Akhil Kondepudi, Alexander Aabedi, Arjun Adapa, Wajd N. Al-Holou, Jason Heth, Oren Sagher, Pedro R. Lowenstein, Maria Castro, Lisa Irina Wadiura, Georg Widhalm, Volker Neuschmelting, David Reinecke, Niklas von Spreckelsen, Mitchel S. Berger, Shawn Hervey-Jumper, John G. Golfinos, Matija Snuderl, Sandra Camelo-Piragua, Christian W. Freudiger, Honglak Lee, Daniel A. Orringer
2023 J jnl
Code Models are Zero-shot Precondition Reasoners.
CoRR
Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu, Anthony Zhe Liu, Dong-Ki Kim, Dongsub Shim, Moontae Lee, Honglak Lee
2023 A* conf
Combining Behaviors with the Successor Features Keyboard.
NeurIPS
Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew K. Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo Jimenez Rezende, Daniel Zoran
2023 J jnl
Combining Behaviors with the Successor Features Keyboard.
CoRR
Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew Kyle Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo J. Rezende, Daniel Zoran
2023 A* conf
Composing Task Knowledge With Modular Successor Feature Approximators.
ICLR
Wilka Carvalho, Angelos Filos, Richard L. Lewis, Honglak Lee, Satinder Singh
2023 J jnl
Composing Task Knowledge with Modular Successor Feature Approximators.
CoRR
Wilka Carvalho, Angelos Filos, Richard L. Lewis, Honglak Lee, Satinder Singh
2023 J jnl
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning.
CoRR
Sungjun Cho, Seunghyuk Cho, Sungwoo Park, Hankook Lee, Honglak Lee, Moontae Lee
2023 A* conf
CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation.
NeurIPS
Sihan Xu, Ziqiao Ma, Yidong Huang, Honglak Lee, Joyce Chai
2023 J jnl
CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation.
CoRR
Sihan Xu, Ziqiao Ma, Yidong Huang, Honglak Lee, Joyce Chai
2023 J jnl
Discriminator-Guided Multi-step Reasoning with Language Models.
CoRR
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
2023 A conf
Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution.
WACV
Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, Tae Hyun Kim
2023 J jnl
Exploring Demonstration Ensembling for In-context Learning.
CoRR
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
2023 — conf
Few-shot Reranking for Multi-hop QA via Language Model Prompting.
ACL (1)
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
2023 — conf
Fine-grained Text Style Transfer with Diffusion-Based Language Models.
RepL4NLP@ACL
Yiwei Lyu, Tiange Luo, Jiacheng Shi, Todd C. Hollon, Honglak Lee
2023 J jnl
Fine-grained Text Style Transfer with Diffusion-Based Language Models.
CoRR
Yiwei Lyu, Tiange Luo, Jiacheng Shi, Todd C. Hollon, Honglak Lee
2023 A* conf
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning.
EMNLP
Zheyuan Zhang, Shane Storks, Fengyuan Hu, Sungryull Sohn, Moontae Lee, Honglak Lee, Joyce Chai
2023 J jnl
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning.
CoRR
Zheyuan Zhang, Shane Storks, Fengyuan Hu, Sungryull Sohn, Moontae Lee, Honglak Lee, Joyce Chai
2023 — conf
GRACE: Discriminator-Guided Chain-of-Thought Reasoning.
EMNLP (Findings)
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
2023 A* conf
Go Beyond Imagination: Maximizing Episodic Reachability with World Models.
ICML
Yao Fu, Run Peng, Honglak Lee
2023 J jnl
Go Beyond Imagination: Maximizing Episodic Reachability with World Models.
CoRR
Yao Fu, Run Peng, Honglak Lee
2023 A* conf
Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters.
AAAI
Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee
2023 A* conf
Guide Your Agent with Adaptive Multimodal Rewards.
NeurIPS
Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee
2023 J jnl
Guide Your Agent with Adaptive Multimodal Rewards.
CoRR
Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee
2023 A* conf
Hierarchical Discriminative Learning Improves Visual Representations of Biomedical Microscopy.
CVPR
Cheng Jiang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Christian W. Freudiger, Daniel A. Orringer, Honglak Lee, Todd C. Hollon
2023 J jnl
Hierarchical discriminative learning improves visual representations of biomedical microscopy.
CoRR
Cheng Jiang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Christian W. Freudiger, Daniel A. Orringer, Honglak Lee, Todd C. Hollon
2023 A conf
Investigation of Training Mute-Expressive End-to-End Speech Separation Networks for an Unknown Number of Speakers.
INTERSPEECH
Younggwan Kim, Hyungjun Lim, Kiho Yeom, Eunjoo Seo, Hoodong Lee, Stanley Jungkyu Choi, Honglak Lee
2023 A* conf
Learning Compositional Tasks from Language Instructions.
AAAI
Lajanugen Logeswaran, Wilka Carvalho, Honglak Lee
2023 J jnl
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers.
CoRR
Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
2023 Misc conf
Lightweight Feature Encoder for Wake-Up Word Detection Based on Self-Supervised Speech Representation.
ICASSP
Hyungjun Lim, Younggwan Kim, Kiho Yeom, Eunjoo Seo, Hoodong Lee, Stanley Jungkyu Choi, Honglak Lee
2023 J jnl
Lightweight feature encoder for wake-up word detection based on self-supervised speech representation.
CoRR
Hyungjun Lim, Younggwan Kim, Kiho Yeom, Eunjoo Seo, Hoodong Lee, Stanley Jungkyu Choi, Honglak Lee
2023 A* conf
Merging Generated and Retrieved Knowledge for Open-Domain QA.
EMNLP
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
2023 J jnl
Merging Generated and Retrieved Knowledge for Open-Domain QA.
CoRR
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
2023 J jnl
MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning.
CoRR
Dong-Ki Kim, Sungryull Sohn, Lajanugen Logeswaran, Dongsub Shim, Honglak Lee
2023 J jnl
Multimodal Subtask Graph Generation from Instructional Videos.
CoRR
Yunseok Jang, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Moontae Lee, Honglak Lee
2023 J jnl
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning.
CoRR
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, Yi Gao, Hailiang Zhang, Yang Yang, Weili Guo, Jianfeng Lu, Youngtaek Oh, Jae-Won Cho, Dong-Jin Kim, In So Kweon, Junmo Kim, Woo-Young Kang, Won Young Jhoo, Byungseok Roh, Jonghwan Mun, Solgil Oh, Kenan Emir Ak, Gwang-Gook Lee, Yan Xu, Mingwei Shen, Kyomin Hwang, Wonsik Shin, Kamin Lee, Wonhark Park, Dongkwan Lee, Nojun Kwak, Yujin Wang, Yimu Wang, Tiancheng Gu, Xingchang Lv, Mingmao Sun
2023 J jnl
Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program.
Trans. Mach. Learn. Res.
Tiange Luo, Honglak Lee, Justin Johnson
2023 A* conf
Preference Transformer: Modeling Human Preferences using Transformers for RL.
ICLR
Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
2023 J jnl
Preference Transformer: Modeling Human Preferences using Transformers for RL.
CoRR
Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
2023 A* conf
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models.
NeurIPS
Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee
2023 J jnl
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models.
CoRR
Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee
2023 A* conf
SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations.
NeurIPS
Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee
2023 A* conf
Scalable 3D Captioning with Pretrained Models.
NeurIPS
Tiange Luo, Chris Rockwell, Honglak Lee, Justin Johnson
2023 J jnl
Scalable 3D Captioning with Pretrained Models.
CoRR
Tiange Luo, Chris Rockwell, Honglak Lee, Justin Johnson
2023 A* conf
Simple and Effective Synthesis of Indoor 3D Scenes.
AAAI
Jing Yu Koh, Harsh Agrawal, Dhruv Batra, Richard Tucker, Austin Waters, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson
2023 A* conf
Story Visualization by Online Text Augmentation with Context Memory.
ICCV
Daechul Ahn, Daneul Kim, Gwangmo Song, Seung Hwan Kim, Honglak Lee, Dongyeop Kang, Jonghyun Choi
2023 J jnl
Story Visualization by Online Text Augmentation with Context Memory.
CoRR
Daechul Ahn, Daneul Kim, Gwangmo Song, Seung Hwan Kim, Honglak Lee, Dongyeop Kang, Jonghyun Choi
2023 A* conf
TOD-Flow: Modeling the Structure of Task-Oriented Dialogues.
EMNLP
Sungryull Sohn, Yiwei Lyu, Anthony Z. Liu, Lajanugen Logeswaran, Dong-Ki Kim, Dongsub Shim, Honglak Lee
2023 J jnl
TOD-Flow: Modeling the Structure of Task-Oriented Dialogues.
CoRR
Sungryull Sohn, Yiwei Lyu, Anthony Z. Liu, Lajanugen Logeswaran, Dong-Ki Kim, Dongsub Shim, Honglak Lee
2023 J jnl
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching.
CoRR
Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee
2023 — conf
Unsupervised Task Graph Generation from Instructional Video Transcripts.
ACL (Findings)
Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee
2023 J jnl
Unsupervised Task Graph Generation from Instructional Video Transcripts.
CoRR
Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee
2022 A* conf
CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition.
NeurIPS
Rodrigo Hormazabal, Changyoung Park, Soonyoung Lee, Sehui Han, Yeonsik Jo, Jaewan Lee, Ahra Jo, Seung Hwan Kim, Jaegul Choo, Moontae Lee, Honglak Lee
2022 — conf
Context aware Named Entity Recognition and Relation Extraction with Domain-specific language model.
CLEF (Working Notes)
Youngrok Jang, Hosung Song, Junho Lee, Gyeonghun Kim, Yireun Kim, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae
2022 J jnl
Environment Generation for Zero-Shot Compositional Reinforcement Learning.
CoRR
Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust
2022 — conf
Extended Overview of ChEMU 2022 Evaluation Campaign: Information Extraction in Chemical Patents.
CLEF (Working Notes)
Yuan Li, Biaoyan Fang, Jiayuan He, Hiyori Yoshikawa, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Zubair Afzal, Zenan Zhai, Kojiro Machi, Masaharu Yoshioka, Youngrok Jang, Hosung Song, Junho Lee, Gyeonghun Kim, Yireun Kim, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae, Darshini Mahendran, Christina Tang, Bridget T. McInnes, Timothy Baldwin, Karin Verspoor
2022 J jnl
Fast Inference and Transfer of Compositional Task Structures for Few-shot Task Generalization.
CoRR
Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee
2022 A conf
Fast inference and transfer of compositional task structures for few-shot task generalization.
UAI
Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee
2022 — conf
Few-shot Subgoal Planning with Language Models.
NAACL-HLT
Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee
2022 J jnl
Few-shot Subgoal Planning with Language Models.
CoRR
Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee
2022 A conf
Fully Convolutional Transformer with Local-Global Attention.
IROS
Sihaeng Lee, Eojindl Yi, Janghyeon Lee, Jinsu Yoo, Honglak Lee, Seung Hwan Kim
2022 J jnl
Grouping-matrix based Graph Pooling with Adaptive Number of Clusters.
CoRR
Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee
2022 J jnl
Is Continual Learning Truly Learning Representations Continually?
CoRR
Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon
2022 A* conf
L-Verse: Bidirectional Generation Between Image and Text.
CVPR
Taehoon Kim, Gwangmo Song, Sihaeng Lee, Sangyun Kim, Yewon Seo, Soonyoung Lee, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae
2022 J jnl
LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA.
CoRR
Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
2022 A* conf
Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks.
AAAI
Yijie Guo, Qiucheng Wu, Honglak Lee
2022 J jnl
Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks.
CoRR
Yijie Guo, Qiucheng Wu, Honglak Lee
2022 A* conf
Learning Parameterized Task Structure for Generalization to Unseen Entities.
AAAI
Anthony Z. Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee
2022 J jnl
Learning Parameterized Task Structure for Generalization to Unseen Entities.
CoRR
Anthony Z. Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee
2022 A* conf
Lipschitz-constrained Unsupervised Skill Discovery.
ICLR
Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim
2022 J jnl
Lipschitz-constrained Unsupervised Skill Discovery.
CoRR
Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim
2022 J jnl
Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program.
CoRR
Tiange Luo, Honglak Lee, Justin Johnson
2022 A* conf
OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology.
NeurIPS
Cheng Jiang, Asadur Chowdury, Xinhai Hou, Akhil Kondepudi, Christian W. Freudiger, Kyle Conway, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd C. Hollon
2022 J jnl
OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology.
CoRR
Cheng Jiang, Asadur Chowdury, Xinhai Hou, Akhil Kondepudi, Christian W. Freudiger, Kyle Conway, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd C. Hollon
2022 A* conf
Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules.
ICML
Juhwan Noh, Dae-Woong Jeong, Kiyoung Kim, Sehui Han, Moontae Lee, Honglak Lee, Yousung Jung
2022 A* conf
Pure Transformers are Powerful Graph Learners.
NeurIPS
Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong
2022 J jnl
Pure Transformers are Powerful Graph Learners.
CoRR
Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong
2022 J jnl
RiCS: A 2D Self-Occlusion Map for Harmonizing Volumetric Objects.
CoRR
Yunseok Jang, Ruben Villegas, Jimei Yang, Duygu Ceylan, Xin Sun, Honglak Lee
2022 J jnl
Rich CNN-Transformer Feature Aggregation Networks for Super-Resolution.
CoRR
Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, Tae Hyun Kim
2022 A* conf
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning.
ICLR
Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
2022 J jnl
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning.
CoRR
Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
2022 J jnl
Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders.
CoRR
Jongseong Jang, Daeun Kyung, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae, Edward Choi
2022 J jnl
Simple and Effective Synthesis of Indoor 3D Scenes.
CoRR
Jing Yu Koh, Harsh Agrawal, Dhruv Batra, Richard Tucker, Austin Waters, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson
2022 A* conf
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching.
NeurIPS
Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee
2022 A* conf
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost.
NeurIPS
Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong
2022 J jnl
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost.
CoRR
Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong
2022 A* conf
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training.
NeurIPS
Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim, Honglak Lee, Junmo Kim
2022 J jnl
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training.
CoRR
Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim, Honglak Lee, Junmo Kim
2021 J jnl
Adversarial Environment Generation for Learning to Navigate the Web.
CoRR
Izzeddin Gur, Natasha Jaques, Kevin Malta, Manoj Tiwari, Honglak Lee, Aleksandra Faust
2021 A* conf
Batch Reinforcement Learning Through Continuation Method.
ICLR
Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen
2021 J jnl
Contrastive Representation Learning for Rapid Intraoperative Diagnosis of Skull Base Tumors Imaged Using Stimulated Raman Histology.
CoRR
Cheng Jiang, Abhishek Bhattacharya, Joseph Linzey, Rushikesh S. Joshi, Sung Jik Cha, Sudharsan Srinivasan, Daniel Alexander Alber, Akhil Kondepudi, Esteban Urias, Balaji Pandian, Wajd N. Al-Holou, Steve Sullivan, B. Gregory Thompson, Jason Heth, Chris Freudiger, Siri S. Khalsa, Donato Pacione, John G. Golfinos, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd C. Hollon
2021 A* conf
Cross-Modal Contrastive Learning for Text-to-Image Generation.
CVPR
Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang
2021 J jnl
Cross-Modal Contrastive Learning for Text-to-Image Generation.
CoRR
Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang
2021 A* conf
Environment Generation for Zero-Shot Compositional Reinforcement Learning.
NeurIPS
Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust
2021 A* conf
Evolving Reinforcement Learning Algorithms.
ICLR
John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust
2021 J jnl
Evolving Reinforcement Learning Algorithms.
CoRR
John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust
2021 A* conf
Improved Consistency Regularization for GANs.
AAAI
Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang
2021 A* conf
Improving Transferability of Representations via Augmentation-Aware Self-Supervision.
NeurIPS
Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin
2021 J jnl
Improving Transferability of Representations via Augmentation-Aware Self-Supervision.
CoRR
Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin
2021 J jnl
L-Verse: Bidirectional Generation Between Image and Text.
CoRR
Taehoon Kim, Gwangmo Song, Sihaeng Lee, Sangyun Kim, Yewon Seo, Soonyoung Lee, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae
2021 A* conf
Learning to Weight Imperfect Demonstrations.
ICML
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
2021 A* conf
Pathdreamer: A World Model for Indoor Navigation.
ICCV
Jing Yu Koh, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson
2021 J jnl
Pathdreamer: A World Model for Indoor Navigation.
CoRR
Jing Yu Koh, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson
2021 A* conf
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment.
IJCAI
Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh
2021 A* conf
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction.
ICLR
Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E. Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong
2021 J jnl
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction.
CoRR
Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E. Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong
2021 A* conf
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks.
ICML
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee
2021 J jnl
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks.
CoRR
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee
2021 A* conf
State Entropy Maximization with Random Encoders for Efficient Exploration.
ICML
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
2021 J jnl
State Entropy Maximization with Random Encoders for Efficient Exploration.
CoRR
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
2021 A* conf
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning.
NeurIPS
Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee
2021 J jnl
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning.
CoRR
Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee
2021 A* conf
Text as Neural Operator: Image Manipulation by Text Instruction.
ACM Multimedia
Tianhao Zhang, Hung-Yu Tseng, Lu Jiang, Weilong Yang, Honglak Lee, Irfan Essa
2021 A conf
Text-to-Image Generation Grounded by Fine-Grained User Attention.
WACV
Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang
2021 J jnl
Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning.
CoRR
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu
2021 A* conf
Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning.
ICML
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu
2021 A* conf
Why Do Better Loss Functions Lead to Less Transferable Features?
NeurIPS
Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi
2021 A* conf
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning.
ICLR
Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
2020 J jnl
An Ode to an ODE.
CoRR
Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
2020 A* conf
BRPO: Batch Residual Policy Optimization.
IJCAI
Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier
2020 J jnl
BRPO: Batch Residual Policy Optimization.
CoRR
Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier
2020 A* conf
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning.
NeurIPS
Guangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang
2020 J jnl
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning.
CoRR
Guangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang
2020 A conf
CompressNet: Generative Compression at Extremely Low Bitrates.
WACV
Shubham Dash, Giridharan Kumaravelu, Vijayakrishna Naganoor, Suraj Kiran Raman, Aditya Ramesh, Honglak Lee
2020 J jnl
CompressNet: Generative Compression at Extremely Low Bitrates.
CoRR
Suraj Kiran Raman, Aditya Ramesh, Vijayakrishna Naganoor, Shubham Dash, Giridharan Kumaravelu, Honglak Lee
2020 A* conf
Consistency Regularization for Generative Adversarial Networks.
ICLR
Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee
2020 A* conf
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning.
ICML
Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin
2020 J jnl
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning.
CoRR
Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin
2020 A* conf
Distilling Effective Supervision From Severe Label Noise.
CVPR
Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister
2020 A* conf
Efficient Adversarial Training With Transferable Adversarial Examples.
CVPR
Haizhong Zheng, Ziqi Zhang, Juncheng Gu, Honglak Lee, Atul Prakash
2020 J jnl
Few-shot Sequence Learning with Transformers.
CoRR
Lajanugen Logeswaran, Ann Lee, Myle Ott, Honglak Lee, Marc'Aurelio Ranzato, Arthur Szlam
2020 — conf
High-Fidelity Synthesis with Disentangled Representation.
ECCV (26)
Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee
2020 J jnl
High-Fidelity Synthesis with Disentangled Representation.
CoRR
Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee
2020 A* conf
How Should an Agent Practice?
AAAI
Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh
2020 J jnl
Improved Consistency Regularization for GANs.
CoRR
Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang
2020 A* conf
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards.
NeurIPS
Yijie Guo, Jongwook Choi, Marcin Moczulski, Shengyu Feng, Samy Bengio, Mohammad Norouzi, Honglak Lee
2020 A* conf
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies.
ICLR
Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee
2020 J jnl
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies.
CoRR
Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee
2020 A* conf
Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning.
ICLR
Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee
2020 A* conf
Ode to an ODE.
NeurIPS
Krzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
2020 A* conf
Predictive Information Accelerates Learning in RL.
NeurIPS
Kuang-Huei Lee, Ian Fischer, Anthony Z. Liu, Yijie Guo, Honglak Lee, John F. Canny, Sergio Guadarrama
2020 J jnl
Predictive Information Accelerates Learning in RL.
CoRR
Kuang-Huei Lee, Ian Fischer, Anthony Z. Liu, Yijie Guo, Honglak Lee, John F. Canny, Sergio Guadarrama
2020 J jnl
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments.
CoRR
Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh
2020 — conf
SemanticAdv: Generating Adversarial Examples via Attribute-Conditioned Image Editing.
ECCV (14)
Haonan Qiu, Chaowei Xiao, Lei Yang, Xinchen Yan, Honglak Lee, Bo Li
2020 J jnl
Text as Neural Operator: Image Manipulation by Text Instruction.
CoRR
Tianhao Zhang, Hung-Yu Tseng, Lu Jiang, Honglak Lee, Irfan Essa, Weilong Yang
2020 J jnl
Text-to-Image Generation Grounded by Fine-Grained User Attention.
CoRR
Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang
2020 J jnl
Time Dependence in Non-Autonomous Neural ODEs.
CoRR
Jared Quincy Davis, Krzysztof Choromanski, Jake Varley, Honglak Lee, Jean-Jacques E. Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia, Vikas Sindhwani
2020 J jnl
Understanding and Diagnosing Vulnerability under Adversarial Attacks.
CoRR
Haizhong Zheng, Ziqi Zhang, Honglak Lee, Atul Prakash
2020 J jnl
What's in a Loss Function for Image Classification?
CoRR
Simon Kornblith, Honglak Lee, Ting Chen, Mohammad Norouzi
2020 J jnl
i-Mix: A Strategy for Regularizing Contrastive Representation Learning.
CoRR
Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
2019 J jnl
A Simple Randomization Technique for Generalization in Deep Reinforcement Learning.
CoRR
Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee
2019 A* conf
Adversarial Defense via Learning to Generate Diverse Attacks.
ICCV
Yunseok Jang, Tianchen Zhao, Seunghoon Hong, Honglak Lee
2019 J jnl
Consistency Regularization for Generative Adversarial Networks.
CoRR
Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee
2019 — conf
Contingency-Aware Exploration in Reinforcement Learning.
ICLR (Poster)
Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee
2019 J jnl
Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks.
CoRR
Xinchen Yan, Mohi Khansari, Jasmine Hsu, Yuanzheng Gong, Yunfei Bai, Sören Pirk, Honglak Lee
2019 — conf
Diversity-Sensitive Conditional Generative Adversarial Networks.
ICLR (Poster)
Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee
2019 J jnl
Diversity-Sensitive Conditional Generative Adversarial Networks.
CoRR
Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee
2019 J jnl
Efficient Adversarial Training with Transferable Adversarial Examples.
CoRR
Haizhong Zheng, Ziqi Zhang, Juncheng Gu, Honglak Lee, Atul Prakash
2019 J jnl
Efficient Exploration with Self-Imitation Learning via Trajectory-Conditioned Policy.
CoRR
Yijie Guo, Jongwook Choi, Marcin Moczulski, Samy Bengio, Mohammad Norouzi, Honglak Lee
2019 A* conf
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks.
NeurIPS
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee
2019 J jnl
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks.
CoRR
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee
2019 J jnl
How Should an Agent Practice?
CoRR
Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh
2019 J jnl
IEG: Robust Neural Network Training to Tackle Severe Label Noise.
CoRR
Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister
2019 — conf
Incremental Learning with Unlabeled Data in the Wild.
CVPR Workshops
Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee
2019 J jnl
Incremental Learning with Unlabeled Data in the Wild.
CoRR
Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee
2019 — ch.
Interpretable Text-to-Image Synthesis with Hierarchical Semantic Layout Generation.
Explainable AI
Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee
2019 A* conf
Learning Latent Dynamics for Planning from Pixels.
ICML
Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson
2019 — conf
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning.
ICLR (Poster)
Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2019 A* conf
Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild.
ICCV
Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee
2019 A* conf
Robust Inference via Generative Classifiers for Handling Noisy Labels.
ICML
Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin
2019 J jnl
Robust Inference via Generative Classifiers for Handling Noisy Labels.
CoRR
Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin
2019 J jnl
SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing.
CoRR
Haonan Qiu, Chaowei Xiao, Lei Yang, Xinchen Yan, Honglak Lee, Bo Li
2019 A* conf
Similarity of Neural Network Representations Revisited.
ICML
Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton
2019 J jnl
Similarity of Neural Network Representations Revisited.
CoRR
Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton
2019 J jnl
Unsupervised Learning of Object Structure and Dynamics from Videos.
CoRR
Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin Murphy, Honglak Lee
2019 A* conf
Unsupervised learning of object structure and dynamics from videos.
NeurIPS
Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee
2019 J jnl
Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?
CoRR
Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine
2019 — conf
Zero-Shot Entity Linking by Reading Entity Descriptions.
ACL (1)
Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee
2019 J jnl
Zero-Shot Entity Linking by Reading Entity Descriptions.
CoRR
Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee
2018 A* conf
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks.
NeurIPS
Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin
2018 J jnl
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks.
CoRR
Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin
2018 A* conf
Addressee and Response Selection in Multi-Party Conversations With Speaker Interaction RNNs.
AAAI
Rui Zhang, Honglak Lee, Lazaros Polymenakos, Dragomir R. Radev
2018 — conf
An efficient framework for learning sentence representations.
ICLR (Poster)
Lajanugen Logeswaran, Honglak Lee
2018 J jnl
An efficient framework for learning sentence representations.
CoRR
Lajanugen Logeswaran, Honglak Lee
2018 A* conf
Content preserving text generation with attribute controls.
NeurIPS
Lajanugen Logeswaran, Honglak Lee, Samy Bengio
2018 J jnl
Content preserving text generation with attribute controls.
CoRR
Lajanugen Logeswaran, Honglak Lee, Samy Bengio
2018 J jnl
Contingency-Aware Exploration in Reinforcement Learning.
CoRR
Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee
2018 A* conf
Data-Efficient Hierarchical Reinforcement Learning.
NeurIPS
Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018 J jnl
Data-Efficient Hierarchical Reinforcement Learning.
CoRR
Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018 J jnl
Generative Adversarial Self-Imitation Learning.
CoRR
Yijie Guo, Junhyuk Oh, Satinder Singh, Honglak Lee
2018 A* conf
Hierarchical Long-term Video Prediction without Supervision.
ICML
Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee
2018 J jnl
Hierarchical Long-term Video Prediction without Supervision.
CoRR
Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee
2018 A* conf
Hierarchical Novelty Detection for Visual Object Recognition.
CVPR
Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee
2018 J jnl
Hierarchical Novelty Detection for Visual Object Recognition.
CoRR
Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee
2018 A* conf
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies.
NeurIPS
Sungryull Sohn, Junhyuk Oh, Honglak Lee
2018 A* conf
Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis.
CVPR
Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee
2018 J jnl
Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis.
CoRR
Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee
2018 A* conf
Learning 6-DOF Grasping Interaction via Deep Geometry-Aware 3D Representations.
ICRA
Xinchen Yan, Jasmine Hsu, Mohammad Khansari, Yunfei Bai, Arkanath Pathak, Abhinav Gupta, James Davidson, Honglak Lee
2018 A* conf
Learning Hierarchical Semantic Image Manipulation through Structured Representations.
NeurIPS
Seunghoon Hong, Xinchen Yan, Thomas E. Huang, Honglak Lee
2018 J jnl
Learning Hierarchical Semantic Image Manipulation through Structured Representations.
CoRR
Seunghoon Hong, Xinchen Yan, Thomas E. Huang, Honglak Lee
2018 J jnl
Learning Latent Dynamics for Planning from Pixels.
CoRR
Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson
2018 — conf
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics.
ECCV (5)
Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, Honglak Lee
2018 J jnl
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics.
CoRR
Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, Honglak Lee
2018 J jnl
Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies.
CoRR
Sungryull Sohn, Junhyuk Oh, Honglak Lee
2018 J jnl
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning.
CoRR
Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018 A* conf
Neural Kinematic Networks for Unsupervised Motion Retargetting.
CVPR
Ruben Villegas, Jimei Yang, Duygu Ceylan, Honglak Lee
2018 J jnl
Neural Kinematic Networks for Unsupervised Motion Retargetting.
CoRR
Ruben Villegas, Jimei Yang, Duygu Ceylan, Honglak Lee
2018 A* conf
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion.
NeurIPS
Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee
2018 J jnl
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion.
CoRR
Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee
2018 A* conf
Self-Imitation Learning.
ICML
Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee
2018 J jnl
Self-Imitation Learning.
CoRR
Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee
2018 A* conf
Sentence Ordering and Coherence Modeling using Recurrent Neural Networks.
AAAI
Lajanugen Logeswaran, Honglak Lee, Dragomir R. Radev
2018 — conf
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples.
ICLR (Poster)
Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin
2018 A* conf
Unsupervised Discovery of Object Landmarks as Structural Representations.
CVPR
Yuting Zhang, Yijie Guo, Yixin Jin, Yijun Luo, Zhiyuan He, Honglak Lee
2018 J jnl
Unsupervised Discovery of Object Landmarks as Structural Representations.
CoRR
Yuting Zhang, Yijie Guo, Yixin Jin, Yijun Luo, Zhiyuan He, Honglak Lee
2017 J jnl
Addressee and Response Selection in Multi-Party Conversations with Speaker Interaction RNNs.
CoRR
Rui Zhang, Honglak Lee, Lazaros Polymenakos, Dragomir R. Radev
2017 — conf
Decomposing Motion and Content for Natural Video Sequence Prediction.
ICLR (Poster)
Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee
2017 J jnl
Decomposing Motion and Content for Natural Video Sequence Prediction.
CoRR
Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee
2017 A* conf
Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries.
CVPR
Yuting Zhang, Luyao Yuan, Yijie Guo, Zhiyuan He, I-An Huang, Honglak Lee
2017 J jnl
Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries.
CoRR
Yuting Zhang, Luyao Yuan, Yijie Guo, Zhiyuan He, I-An Huang, Honglak Lee
2017 A conf
Exploring the structure of a real-time, arbitrary neural artistic stylization network.
BMVC
Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens
2017 J jnl
Exploring the structure of a real-time, arbitrary neural artistic stylization network.
CoRR
Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens
2017 J jnl
Learning Grasping Interaction with Geometry-aware 3D Representations.
CoRR
Xinchen Yan, Mohi Khansari, Yunfei Bai, Jasmine Hsu, Arkanath Pathak, Abhinav Gupta, James Davidson, Honglak Lee
2017 A* conf
Learning to Generate Long-term Future via Hierarchical Prediction.
ICML
Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee
2017 J jnl
Learning to Generate Long-term Future via Hierarchical Prediction.
CoRR
Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee
2017 A* conf
Towards Understanding the Invertibility of Convolutional Neural Networks.
IJCAI
Anna C. Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee
2017 J jnl
Towards Understanding the Invertibility of Convolutional Neural Networks.
CoRR
Anna C. Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee
2017 J jnl
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples.
CoRR
Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin
2017 — conf
Value Prediction Network.
NIPS
Junhyuk Oh, Satinder Singh, Honglak Lee
2017 J jnl
Value Prediction Network.
CoRR
Junhyuk Oh, Satinder Singh, Honglak Lee
2017 A* conf
Weakly Supervised Semantic Segmentation Using Web-Crawled Videos.
CVPR
Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han
2017 J jnl
Weakly Supervised Semantic Segmentation using Web-Crawled Videos.
CoRR
Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han
2017 A* conf
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning.
ICML
Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli
2017 J jnl
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning.
CoRR
Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli
2016 — conf
Attribute2Image: Conditional Image Generation from Visual Attributes.
ECCV (4)
Xinchen Yan, Jimei Yang, Kihyuk Sohn, Honglak Lee
2016 A* conf
Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification.
ICML
Yuting Zhang, Kibok Lee, Honglak Lee
2016 J jnl
Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification.
CoRR
Yuting Zhang, Kibok Lee, Honglak Lee
2016 A* conf
Control of Memory, Active Perception, and Action in Minecraft.
ICML
Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee
2016 J jnl
Control of Memory, Active Perception, and Action in Minecraft.
CoRR
Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee
2016 A* conf
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games.
IJCAI
Xiaoxiao Guo, Satinder Singh, Richard L. Lewis, Honglak Lee
2016 J jnl
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games.
CoRR
Xiaoxiao Guo, Satinder Singh, Richard L. Lewis, Honglak Lee
2016 J jnl
Deep Variational Canonical Correlation Analysis.
CoRR
Weiran Wang, Honglak Lee, Karen Livescu
2016 — conf
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents.
HLT-NAACL
Rui Zhang, Honglak Lee, Dragomir R. Radev
2016 J jnl
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents.
CoRR
Rui Zhang, Honglak Lee, Dragomir R. Radev
2016 A conf
Discriminative Training of Structured Dictionaries via Block Orthogonal Matching Pursuit.
SDM
Wenling Shang, Kihyuk Sohn, Honglak Lee, Anna C. Gilbert
2016 A* conf
Generative Adversarial Text to Image Synthesis.
ICML
Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee
2016 J jnl
Generative Adversarial Text to Image Synthesis.
CoRR
Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee
2016 A* conf
Learning Deep Representations of Fine-Grained Visual Descriptions.
CVPR
Scott E. Reed, Zeynep Akata, Honglak Lee, Bernt Schiele
2016 J jnl
Learning Deep Representations of Fine-grained Visual Descriptions.
CoRR
Scott E. Reed, Zeynep Akata, Bernt Schiele, Honglak Lee
2016 A* conf
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network.
CVPR
Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han
2016 — conf
Learning What and Where to Draw.
NIPS
Scott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee
2016 J jnl
Learning What and Where to Draw.
CoRR
Scott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee
2016 A* conf
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network.
CVPR
Jimei Yang, Brian L. Price, Scott Cohen, Honglak Lee, Ming-Hsuan Yang
2016 J jnl
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network.
CoRR
Jimei Yang, Brian L. Price, Scott Cohen, Honglak Lee, Ming-Hsuan Yang
2016 — conf
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision.
NIPS
Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee
2016 J jnl
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision.
CoRR
Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee
2016 J jnl
Sentence Ordering using Recurrent Neural Networks.
CoRR
Lajanugen Logeswaran, Honglak Lee, Dragomir R. Radev
2016 A* conf
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units.
ICML
Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee
2016 J jnl
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units.
CoRR
Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee
2016 J jnl
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis.
CoRR
Jimei Yang, Scott E. Reed, Ming-Hsuan Yang, Honglak Lee
2015 — conf
A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks.
EMBC
Changhan Wang, Xinchen Yan, Max Olan Smith, Kanika Kochhar, Marcie Rubin, Stephen M. Warren, James S. Wrobel, Honglak Lee
2015 — conf
Action-Conditional Video Prediction using Deep Networks in Atari Games.
NIPS
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh
2015 J jnl
Action-Conditional Video Prediction using Deep Networks in Atari Games.
CoRR
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh
2015 J jnl
Attribute2Image: Conditional Image Generation from Visual Attributes.
CoRR
Xinchen Yan, Jimei Yang, Kihyuk Sohn, Honglak Lee
2015 — conf
Deep Visual Analogy-Making.
NIPS
Scott E. Reed, Yi Zhang, Yuting Zhang, Honglak Lee
2015 J jnl
Deep learning for detecting robotic grasps.
Int. J. Robotics Res.
Ian Lenz, Honglak Lee, Ashutosh Saxena
2015 J jnl
Editorial introduction to the Neural Networks special issue on Deep Learning of Representations.
Neural Networks
Yoshua Bengio, Honglak Lee
2015 A* conf
Evaluation of output embeddings for fine-grained image classification.
CVPR
Zeynep Akata, Scott E. Reed, Daniel Walter, Honglak Lee, Bernt Schiele
2015 J jnl
Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction.
CoRR
Yuting Zhang, Kihyuk Sohn, Ruben Villegas, Gang Pan, Honglak Lee
2015 A* conf
Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction.
CVPR
Yuting Zhang, Kihyuk Sohn, Ruben Villegas, Gang Pan, Honglak Lee
2015 — conf
Learning Structured Output Representation using Deep Conditional Generative Models.
NIPS
Kihyuk Sohn, Honglak Lee, Xinchen Yan
2015 J jnl
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network.
CoRR
Seunghoon Hong, Junhyuk Oh, Bohyung Han, Honglak Lee
2015 — conf
Training Deep Neural Networks on Noisy Labels with Bootstrapping.
ICLR (Workshop)
Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich
2015 — conf
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis.
NIPS
Jimei Yang, Scott E. Reed, Ming-Hsuan Yang, Honglak Lee
2014 — conf
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning.
NIPS
Xiaoxiao Guo, Satinder Singh, Honglak Lee, Richard L. Lewis, Xiaoshi Wang
2014 — conf
Improved Multimodal Deep Learning with Variation of Information.
NIPS
Kihyuk Sohn, Wenling Shang, Honglak Lee
2014 A* conf
Learning to Disentangle Factors of Variation with Manifold Interaction.
ICML
Scott E. Reed, Kihyuk Sohn, Yuting Zhang, Honglak Lee
2014 A* conf
Structured Recurrent Temporal Restricted Boltzmann Machines.
ICML
Roni Mittelman, Benjamin Kuipers, Silvio Savarese, Honglak Lee
2014 J jnl
Zero-Shot Learning with Structured Embeddings.
CoRR
Zeynep Akata, Honglak Lee, Bernt Schiele
2013 — conf
Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising.
NIPS
Forest Agostinelli, Michael R. Anderson, Honglak Lee
2013 A* conf
Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling.
CVPR
Andrew Kae, Kihyuk Sohn, Honglak Lee, Erik G. Learned-Miller
2013 — conf
Deep Learning for Detecting Robotic Grasps
ICLR (Workshop)
Ian Lenz, Honglak Lee, Ashutosh Saxena
2013 — conf
Deep Learning for Detecting Robotic Grasps.
Robotics: Science and Systems
Ian Lenz, Honglak Lee, Ashutosh Saxena
2013 Misc conf
Deep learning for robust feature generation in audiovisual emotion recognition.
ICASSP
Yelin Kim, Honglak Lee, Emily Mower Provost
2013 J jnl
Guest Editors' Introduction: Special Section on Learning Deep Architectures.
IEEE Trans. Pattern Anal. Mach. Intell.
Samy Bengio, Li Deng, Hugo Larochelle, Honglak Lee, Ruslan Salakhutdinov
2013 — conf
Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines.
ICML (2)
Kihyuk Sohn, Guanyu Zhou, Chansoo Lee, Honglak Lee
2013 A* conf
Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines.
CVPR
Roni Mittelman, Honglak Lee, Benjamin Kuipers, Silvio Savarese
2012 A* conf
An efficient branch-and-bound algorithm for optimal human pose estimation.
CVPR
Min Sun, Murali Telaprolu, Honglak Lee, Silvio Savarese
2012 A conf
Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers.
AISTATS
Caoxie Zhang, Honglak Lee, Kang G. Shin
2012 A conf
Efficient and Exact MAP-MRF Inference using Branch and Bound.
AISTATS
Min Sun, Murali Telaprolu, Honglak Lee, Silvio Savarese
2012 A* conf
Learning Invariant Representations with Local Transformations.
ICML
Kihyuk Sohn, Honglak Lee
2012 A* conf
Learning hierarchical representations for face verification with convolutional deep belief networks.
CVPR
Gary B. Huang, Honglak Lee, Erik G. Learned-Miller
2012 — conf
Learning to Align from Scratch.
NIPS
Gary B. Huang, Marwan A. Mattar, Honglak Lee, Erik G. Learned-Miller
2012 A conf
Online Incremental Feature Learning with Denoising Autoencoders.
AISTATS
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
2011 — conf
A Classification-Based Polyphonic Piano Transcription Approach Using Learned Feature Representations.
ISMIR
Juhan Nam, Jiquan Ngiam, Honglak Lee, Malcolm Slaney
2011 A conf
An Analysis of Single-Layer Networks in Unsupervised Feature Learning.
AISTATS
Adam Coates, Andrew Y. Ng, Honglak Lee
2011 A* conf
Efficient learning of sparse, distributed, convolutional feature representations for object recognition.
ICCV
Kihyuk Sohn, Dae Yon Jung, Honglak Lee, Alfred O. Hero III
2011 A* conf
Multimodal Deep Learning.
ICML
Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, Andrew Y. Ng
2011 J jnl
Unsupervised learning of hierarchical representations with convolutional deep belief networks.
Commun. ACM
Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng
2010 A* conf
An integrated machine learning approach to stroke prediction.
KDD
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Kuang Chiu, Junling Hu, Honglak Lee
2010 — —
Unsupervised feature learning via sparse hierarchical representations.
Honglak Lee
2009 A* conf
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations.
ICML
Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng
2009 A* conf
Exponential Family Sparse Coding with Application to Self-taught Learning.
IJCAI
Honglak Lee, Rajat Raina, Alex Teichman, Andrew Y. Ng
2009 — conf
Measuring Invariances in Deep Networks.
NIPS
Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee, Andrew Y. Ng
2009 — conf
Unsupervised feature learning for audio classification using convolutional deep belief networks.
NIPS
Honglak Lee, Peter T. Pham, Yan Largman, Andrew Y. Ng
2007 A* conf
Self-taught learning: transfer learning from unlabeled data.
ICML
Rajat Raina, Alexis J. Battle, Honglak Lee, Benjamin Packer, Andrew Y. Ng
2007 — conf
Sparse deep belief net model for visual area V2.
NIPS
Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng
2006 — conf
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image.
CVPR (2)
Erick Delage, Honglak Lee, Andrew Y. Ng
2006 A* conf
Efficient L1 Regularized Logistic Regression.
AAAI
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. Ng
2006 — conf
Efficient sparse coding algorithms.
NIPS
Honglak Lee, Alexis J. Battle, Rajat Raina, Andrew Y. Ng
2006 A* conf
Quadruped Robot Obstacle Negotiation via Reinforcement Learning.
ICRA
Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, Andrew Y. Ng
2005 C conf
Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes.
ISRR
Erick Delage, Honglak Lee, Andrew Y. Ng
2005 — conf
Spam Deobfuscation using a Hidden Markov Model.
CEAS
Honglak Lee, Andrew Y. Ng