Le Hou - RankMe

59 papers A* 10A 2Journal 36Unranked 11

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Capabilities of Gemini Models in Medicine. CoRR Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan
2024	—	`conf`	Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning. EMNLP (Findings) Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent
2024	J	`jnl`	Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning. CoRR Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent
2024	—	`conf`	Distilling Text Style Transfer With Self-Explanation From LLMs. NAACL (Student Research Workshop) Chiyu Zhang, Honglong Cai, Yuezhang Li, Yuexin Wu, Le Hou, Muhammad Abdul-Mageed
2024	J	`jnl`	Distilling Text Style Transfer With Self-Explanation From LLMs. CoRR Chiyu Zhang, Honglong Cai, Yuezhang Li, Yuexin Wu, Le Hou, Muhammad Abdul-Mageed
2024	A*	`conf`	Enabling Lanuguage Models to Implicitly Learn Self-Improvement. ICLR Ziqi Wang, Le Hou, Tianjian Lu, Yuexin Wu, Yunxuan Li, Hongkun Yu, Heng Ji
2024	—	`conf`	Improving Multi-Agent Debate with Sparse Communication Topology. EMNLP (Findings) Yunxuan Li, Yibing Du, Jiageng Zhang, Le Hou, Peter Grabowski, Yeqing Li, Eugene Ie
2024	J	`jnl`	Improving Multi-Agent Debate with Sparse Communication Topology. CoRR Yunxuan Li, Yibing Du, Jiageng Zhang, Le Hou, Peter Grabowski, Yeqing Li, Eugene Ie
2024	A*	`conf`	Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models. ICLR Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y. Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou
2024	—	`conf`	Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision. EMNLP (Findings) Zihan Wang, Yunxuan Li, Yuexin Wu, Liangchen Luo, Le Hou, Hongkun Yu, Jingbo Shang
2024	J	`jnl`	Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision. CoRR Zihan Wang, Yunxuan Li, Yuexin Wu, Liangchen Luo, Le Hou, Hongkun Yu, Jingbo Shang
2024	J	`jnl`	NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. CoRR Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou
2024	J	`jnl`	Scaling Instruction-Finetuned Language Models. J. Mach. Learn. Res. Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei
2024	J	`jnl`	Towards Conversational Diagnostic AI. CoRR Tao Tu, Anil Palepu, Mike Schaekermann, Khaled Saab, Jan Freyberg, Ryutaro Tanno, Amy Wang, Brenna Li, Mohamed Amin, Nenad Tomasev, Shekoofeh Azizi, Karan Singhal, Yong Cheng, Le Hou, Albert Webson, Kavita Kulkarni, S. Sara Mahdavi, Christopher Semturs, Juraj Gottweis, Joelle K. Barral, Katherine Chou, Gregory S. Corrado, Yossi Matias, Alan Karthikesalingam, Vivek Natarajan
2023	A*	`conf`	Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. ICLR Ziqi Wang, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji
2023	J	`jnl`	Enable Language Models to Implicitly Learn Self-Improvement From Data. CoRR Ziqi Wang, Le Hou, Tianjian Lu, Yuexin Wu, Yunxuan Li, Hongkun Yu, Heng Ji
2023	—	`conf`	Few Shot Hematopoietic Cell Classification. MIDL Vu Nguyen, Prantik Howlader, Le Hou, Dimitris Samaras, Rajarsi R. Gupta, Joel H. Saltz
2023	J	`jnl`	Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts. CoRR Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y. Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou
2023	J	`jnl`	Instruction-Following Evaluation for Large Language Models. CoRR Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, Siddhartha Brahma, Sujoy Basu, Yi Luan, Denny Zhou, Le Hou
2023	A*	`conf`	Large Language Models Can Self-Improve. EMNLP Jiaxin Huang, Shixiang Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
2023	A*	`conf`	Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi
2023	A*	`conf`	Symbol tuning improves in-context learning in language models. EMNLP Jerry W. Wei, Le Hou, Andrew K. Lampinen, Xiangning Chen, Da Huang, Yi Tay, Xinyun Chen, Yifeng Lu, Denny Zhou, Tengyu Ma, Quoc V. Le
2023	J	`jnl`	Symbol tuning improves in-context learning in language models. CoRR Jerry W. Wei, Le Hou, Andrew K. Lampinen, Xiangning Chen, Da Huang, Yi Tay, Xinyun Chen, Yifeng Lu, Denny Zhou, Tengyu Ma, Quoc V. Le
2023	A*	`conf`	The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. ICML Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, Adam Roberts
2023	J	`jnl`	The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. CoRR Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, Adam Roberts
2023	J	`jnl`	Towards Accurate Differential Diagnosis with Large Language Models. CoRR Daniel McDuff, Mike Schaekermann, Tao Tu, Anil Palepu, Amy Wang, Jake Garrison, Karan Singhal, Yash Sharma, Shekoofeh Azizi, Kavita Kulkarni, Le Hou, Yong Cheng, Yun Liu, S. Sara Mahdavi, Sushant Prakash, Anupam Pathak, Christopher Semturs, Shwetak N. Patel, Dale R. Webster, Ewa Dominowska, Juraj Gottweis, Joelle K. Barral, Katherine Chou, Gregory S. Corrado, Yossi Matias, Jake Sunshine, Alan Karthikesalingam, Vivek Natarajan
2023	J	`jnl`	Towards Expert-Level Medical Question Answering with Large Language Models. CoRR Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, Mike Schaekermann, Amy Wang, Mohamed Amin, Sami Lachgar, Philip Andrew Mansfield, Sushant Prakash, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Nenad Tomasev, Yun Liu, Renee Wong, Christopher Semturs, S. Sara Mahdavi, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Shekoofeh Azizi, Alan Karthikesalingam, Vivek Natarajan
2022	J	`jnl`	Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. CoRR Ziqi Wang, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji
2022	J	`jnl`	Large Language Models Can Self-Improve. CoRR Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
2022	J	`jnl`	Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi
2022	J	`jnl`	Scaling Instruction-Finetuned Language Models. CoRR Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei
2022	—	`conf`	Token Dropping for Efficient BERT Pretraining. ACL (1) Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou
2022	J	`jnl`	Token Dropping for Efficient BERT Pretraining. CoRR Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou
2021	J	`jnl`	Large Scale Shadow Annotation and Detection Using Lazy Annotation and Stacked CNNs. IEEE Trans. Pattern Anal. Mach. Intell. Le Hou, Tomás F. Yago Vicente, Minh Hoai, Dimitris Samaras
2021	J	`jnl`	Speeding up Deep Model Training by Sharing Weights and Then Unsharing. CoRR Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou
2020	J	`jnl`	Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types. CoRR Le Hou, Rajarsi Gupta, John S. Van Arnam, Yuwei Zhang, Kaustubh Sivalenka, Dimitris Samaras, Tahsin M. Kurç, Joel H. Saltz
2020	J	`jnl`	Talking-Heads Attention. CoRR Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou
2020	—	`conf`	Weakly-Supervised Deep Stain Decomposition for Multiplex IHC Images. ISBI Shahira Abousamra, Danielle Fassler, Le Hou, Yuwei Zhang, Rajarsi Gupta, Tahsin M. Kurç, Luisa F. Escobar-Hoyos, Dimitris Samaras, Beatrice Knudson, Kenneth Shroyer, Joel H. Saltz, Chao Chen
2019	—	`conf`	Exascale Deep Learning to Accelerate Cancer Research. IEEE BigData Robert M. Patton, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou
2019	J	`jnl`	Exascale Deep Learning to Accelerate Cancer Research. CoRR Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz
2019	—	`conf`	From Whole Slide Tissues to Knowledge: Mapping Sub-cellular Morphology of Cancer. BrainLes@MICCAI (2) Tahsin M. Kurç, Ashish Sharma, Rajarsi Gupta, Le Hou, Han Le, Shahira Abousamra, Erich Bremer, Ryan Birmingham, Tammy DiPrima, Nan Li, Feiqiao Wang, Joseph Balsamo, Whitney Bremer, Dimitris Samaras, Joel H. Saltz
2019	J	`jnl`	High Resolution Medical Image Analysis with Spatial Partitioning. CoRR Le Hou, Youlong Cheng, Noam Shazeer, Niki Parmar, Yeqing Li, Panagiotis Korfiatis, Travis M. Drucker, Daniel J. Blezek, Xiaodan Song
2019	J	`jnl`	Label Super Resolution with Inter-Instance Loss. CoRR Maozheng Zhao, Le Hou, Han Le, Dimitris Samaras, Nebojsa Jojic, Danielle Fassler, Tahsin M. Kurç, Rajarsi R. Gupta, Kolya Malkin, Shahira Abousamra, Kenneth Shroyer, Joel H. Saltz
2019	—	`conf`	Label super-resolution networks. ICLR (Poster) Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel H. Saltz, Lucas Joppa, Nebojsa Jojic
2019	A*	`conf`	Large Scale High-Resolution Land Cover Mapping With Multi-Resolution Data. CVPR Caleb Robinson, Le Hou, Kolya Malkin, Rachel Soobitsky, Jacob Czawlytko, Bistra Dilkina, Nebojsa Jojic
2019	J	`jnl`	Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types. CoRR Shahira Abousamra, Le Hou, Rajarsi R. Gupta, Chao Chen, Dimitris Samaras, Tahsin M. Kurç, Rebecca Batiste, Tianhao Zhao, Kenneth Shroyer, Joel H. Saltz
2019	A*	`conf`	Robust Histopathology Image Analysis: To Label or to Synthesize? CVPR Le Hou, Ayush Agarwal, Dimitris Samaras, Tahsin M. Kurç, Rajarsi R. Gupta, Joel H. Saltz
2019	J	`jnl`	Sparse autoencoder for unsupervised nucleus detection and representation in histopathology images. Pattern Recognit. Le Hou, Vu Nguyen, Ariel B. Kanevsky, Dimitris Samaras, Tahsin M. Kurç, Tianhao Zhao, Rajarsi R. Gupta, Yi Gao, Wenjin Chen, David J. Foran, Joel H. Saltz
2019	J	`jnl`	Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer. CoRR Han Le, Rajarsi R. Gupta, Le Hou, Shahira Abousamra, Danielle Fassler, Tahsin M. Kurç, Dimitris Samaras, Rebecca Batiste, Tianhao Zhao, Alison L. Van Dyke, Ashish Sharma, Erich Bremer, Jonas S. Almeida, Joel H. Saltz
2017	A	`conf`	Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images. WACV Veda Murthy, Le Hou, Dimitris Samaras, Tahsin M. Kurç, Joel H. Saltz
2017	A	`conf`	ConvNets with Smooth Adaptive Activation Functions for Regression. AISTATS Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Joel H. Saltz
2017	J	`jnl`	Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images. CoRR Le Hou, Vu Nguyen, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Tianhao Zhao, Joel H. Saltz
2017	J	`jnl`	Unsupervised Histopathology Image Synthesis. CoRR Le Hou, Ayush Agarwal, Dimitris Samaras, Tahsin M. Kurç, Rajarsi R. Gupta, Joel H. Saltz
2016	J	`jnl`	Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images. CoRR Veda Murthy, Le Hou, Dimitris Samaras, Tahsin M. Kurç, Joel H. Saltz
2016	—	`conf`	Large-Scale Training of Shadow Detectors with Noisily-Annotated Shadow Examples. ECCV (6) Tomás F. Yago Vicente, Le Hou, Chen-Ping Yu, Minh Hoai, Dimitris Samaras
2016	J	`jnl`	Neural Networks with Smooth Adaptive Activation Functions for Regression. CoRR Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Joel H. Saltz
2016	A*	`conf`	Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification. CVPR Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, James E. Davis, Joel H. Saltz
2016	J	`jnl`	Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks. CoRR Le Hou, Chen-Ping Yu, Dimitris Samaras
2015	J	`jnl`	Efficient Multiple Instance Convolutional Neural Networks for Gigapixel Resolution Image Classification. CoRR Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, James E. Davis, Joel H. Saltz