Efficient Multiple Instance Convolutional Neural Networks for Gigapixel Resolution Image Classification. - Le Hou; Dimitris Samaras; Tahsin M. Kurç; Yi Gao 002; James E. Davis; Joel H. Saltz (CoRR, 2015)

Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification. - Le Hou; Dimitris Samaras; Tahsin M. Kurç; Yi Gao 002; James E. Davis; Joel H. Saltz (CVPR, 2016)

Large-Scale Training of Shadow Detectors with Noisily-Annotated Shadow Examples. - Tomás F. Yago Vicente; Le Hou; Chen-Ping Yu; Minh Hoai; Dimitris Samaras (ECCV (6), 2016)

Neural Networks with Smooth Adaptive Activation Functions for Regression. - Le Hou; Dimitris Samaras; Tahsin M. Kurç; Yi Gao 002; Joel H. Saltz (CoRR, 2016)

Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks. - Le Hou; Chen-Ping Yu; Dimitris Samaras (CoRR, 2016)

ConvNets with Smooth Adaptive Activation Functions for Regression. - Le Hou; Dimitris Samaras; Tahsin M. Kurç; Yi Gao 002; Joel H. Saltz (AISTATS, 2017)

Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images. - Veda Murthy; Le Hou; Dimitris Samaras; Tahsin M. Kurç; Joel H. Saltz (WACV, 2017)

Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images. - Le Hou; Vu Nguyen 004; Dimitris Samaras; Tahsin M. Kurç; Yi Gao 002; Tianhao Zhao; Joel H. Saltz (CoRR, 2017)

Unsupervised Histopathology Image Synthesis. - Le Hou; Ayush Agarwal; Dimitris Samaras; Tahsin M. Kurç; Rajarsi R. Gupta; Joel H. Saltz (CoRR, 2017)

Exascale Deep Learning to Accelerate Cancer Research. - 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 (IEEE BigData, 2019)

From Whole Slide Tissues to Knowledge: Mapping Sub-cellular Morphology of Cancer. - Tahsin M. Kurç; Ashish Sharma 001; Rajarsi Gupta 001; Le Hou; Han Le; Shahira Abousamra; Erich Bremer; Ryan Birmingham; Tammy Diprima; Nan Li; Feiqiao Wang; Joseph Balsamo; et al. (BrainLes@MICCAI (2), 2019)

Robust Histopathology Image Analysis: To Label or to Synthesize? - Le Hou; Ayush Agarwal; Dimitris Samaras; Tahsin M. Kurç; Rajarsi R. Gupta; Joel H. Saltz (CVPR, 2019)

Large Scale High-Resolution Land Cover Mapping With Multi-Resolution Data. - Caleb Robinson; Le Hou; Kolya Malkin; Rachel Soobitsky; Jacob Czawlytko; Bistra Dilkina; Nebojsa Jojic (CVPR, 2019)

Label super-resolution networks. - Kolya Malkin; Caleb Robinson; Le Hou; Rachel Soobitsky; Jacob Czawlytko; Dimitris Samaras; Joel H. Saltz; Lucas Joppa; Nebojsa Jojic (ICLR (Poster), 2019)

Label Super Resolution with Inter-Instance Loss. - 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 (CoRR, 2019)

Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer. - 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 001; Erich Bremer; et al. (CoRR, 2019)

Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types. - Shahira Abousamra; Le Hou; Rajarsi R. Gupta; Chao Chen 012; Dimitris Samaras; Tahsin M. Kurç; Rebecca Batiste; Tianhao Zhao; Kenneth Shroyer; Joel H. Saltz (CoRR, 2019)

High Resolution Medical Image Analysis with Spatial Partitioning. - Le Hou; Youlong Cheng; Noam Shazeer; Niki Parmar; Yeqing Li; Panagiotis Korfiatis; Travis M. Drucker; Daniel J. Blezek; Xiaodan Song (CoRR, 2019)

Sparse autoencoder for unsupervised nucleus detection and representation in histopathology images. - Le Hou; Vu Nguyen 004; Ariel B. Kanevsky; Dimitris Samaras; Tahsin M. Kurç; Tianhao Zhao; Rajarsi R. Gupta; Yi Gao 002; Wenjin Chen; David J. Foran; Joel H. Saltz (Pattern Recognit., 2019)

Weakly-Supervised Deep Stain Decomposition for Multiplex IHC Images. - Shahira Abousamra; Danielle Fassler; Le Hou; Yuwei Zhang; Rajarsi Gupta 001; Tahsin M. Kurç; Luisa F. Escobar-Hoyos; Dimitris Samaras; Beatrice Knudson; Kenneth Shroyer; Joel H. Saltz; Chao Chen 012 (ISBI, 2020)

Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types. - Le Hou; Rajarsi Gupta 001; John S. Van Arnam; Yuwei Zhang; Kaustubh Sivalenka; Dimitris Samaras; Tahsin M. Kurç; Joel H. Saltz (CoRR, 2020)

Talking-Heads Attention. - Noam Shazeer; Zhenzhong Lan; Youlong Cheng; Nan Ding 002; Le Hou (CoRR, 2020)

Speeding up Deep Model Training by Sharing Weights and Then Unsharing. - Shuo Yang; Le Hou; Xiaodan Song; Qiang Liu 001; Denny Zhou (CoRR, 2021)

Large Scale Shadow Annotation and Detection Using Lazy Annotation and Stacked CNNs. - Le Hou; Tomás F. Yago Vicente; Minh Hoai; Dimitris Samaras (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Token Dropping for Efficient BERT Pretraining. - Le Hou; Richard Yuanzhe Pang; Tianyi Zhou 001; Yuexin Wu; Xinying Song; Xiaodan Song; Denny Zhou (ACL (1), 2022)

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. - Denny Zhou; Nathanael Schärli; Le Hou; Jason Wei; Nathan Scales; Xuezhi Wang 002; Dale Schuurmans; Olivier Bousquet; Quoc Le 001; Ed H. Chi (CoRR, 2022)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Eric Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (CoRR, 2022)

Large Language Models Can Self-Improve. - Jiaxin Huang 001; Shixiang Gu; Le Hou; Yuexin Wu; Xuezhi Wang 002; Hongkun Yu 001; Jiawei Han 001 (EMNLP, 2023)

Symbol tuning improves in-context learning in language models. - Jerry W. Wei; Le Hou; Andrew K. Lampinen; Xiangning Chen; Da Huang; Yi Tay; Xinyun Chen; Yifeng Lu; Denny Zhou; Tengyu Ma 001; Quoc V. Le (EMNLP, 2023)

Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. - Ziqi Wang 003; Yuexin Wu; Frederick Liu; Daogao Liu; Le Hou; Hongkun Yu 001; Jing Li 049; Heng Ji 001 (ICLR, 2023)

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. - Denny Zhou; Nathanael Schärli; Le Hou; Jason Wei; Nathan Scales; Xuezhi Wang 002; Dale Schuurmans; Claire Cui; Olivier Bousquet; Quoc V. Le; Ed H. Chi (ICLR, 2023)

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. - Shayne Longpre; Le Hou; Tu Vu; Albert Webson; Hyung Won Chung; Yi Tay; Denny Zhou; Quoc V. Le; Barret Zoph; Jason Wei; Adam Roberts (ICML, 2023)

Few Shot Hematopoietic Cell Classification. - Vu Nguyen 004; Prantik Howlader; Le Hou; Dimitris Samaras; Rajarsi R. Gupta; Joel H. Saltz (MIDL, 2023)

Towards Expert-Level Medical Question Answering with Large Language Models. - Karan Singhal; Tao Tu 001; Juraj Gottweis; Rory Sayres; Ellery Wulczyn; Le Hou; Kevin Clark; Stephen Pfohl; Heather Cole-Lewis; Darlene Neal; Mike Schaekermann; Amy Wang; et al. (CoRR, 2023)

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts. - Sheng Shen 001; Le Hou; Yanqi Zhou; Nan Du 002; Shayne Longpre; Jason Wei; Hyung Won Chung; Barret Zoph; William Fedus; Xinyun Chen; Tu Vu; Yuexin Wu; et al. (CoRR, 2023)

Enable Language Models to Implicitly Learn Self-Improvement From Data. - Ziqi Wang 003; Le Hou; Tianjian Lu; Yuexin Wu; Yunxuan Li; Hongkun Yu 001; Heng Ji 001 (CoRR, 2023)

Instruction-Following Evaluation for Large Language Models. - Jeffrey Zhou; Tianjian Lu; Swaroop Mishra; Siddhartha Brahma; Sujoy Basu; Yi Luan; Denny Zhou; Le Hou (CoRR, 2023)

Towards Accurate Differential Diagnosis with Large Language Models. - Daniel McDuff; Mike Schaekermann; Tao Tu 001; Anil Palepu; Amy Wang; Jake Garrison; Karan Singhal; Yash Sharma; Shekoofeh Azizi; Kavita Kulkarni; Le Hou; Yong Cheng; et al. (CoRR, 2023)

Improving Multi-Agent Debate with Sparse Communication Topology. - Yunxuan Li; Yibing Du; Jiageng Zhang; Le Hou; Peter Grabowski; Yeqing Li; Eugene Ie (EMNLP (Findings), 2024)

Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning. - Kaiwen Wang; Rahul Kidambi; Ryan Sullivan; Alekh Agarwal; Christoph Dann; Andrea Michi; Marco Gelmi; Yunxuan Li; Raghav Gupta; Avinava Dubey; Alexandre Ramé; Johan Ferret; et al. (EMNLP (Findings), 2024)

Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision. - Zihan Wang 001; Yunxuan Li; Yuexin Wu; Liangchen Luo; Le Hou; Hongkun Yu 001; Jingbo Shang (EMNLP (Findings), 2024)

Enabling Lanuguage Models to Implicitly Learn Self-Improvement. - Ziqi Wang 003; Le Hou; Tianjian Lu; Yuexin Wu; Yunxuan Li; Hongkun Yu 001; Heng Ji 001 (ICLR, 2024)

Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models. - Sheng Shen 001; Le Hou; Yanqi Zhou; Nan Du 002; Shayne Longpre; Jason Wei; Hyung Won Chung; Barret Zoph; William Fedus; Xinyun Chen; Tu Vu; Yuexin Wu; et al. (ICLR, 2024)

Distilling Text Style Transfer With Self-Explanation From LLMs. - Chiyu Zhang; Honglong Cai; Yuezhang Li; Yuexin Wu; Le Hou; Muhammad Abdul-Mageed (NAACL (Student Research Workshop), 2024)

Towards Conversational Diagnostic AI. - Tao Tu 001; Anil Palepu; Mike Schaekermann; Khaled Saab 003; Jan Freyberg; Ryutaro Tanno; Amy Wang; Brenna Li; Mohamed Amin; Nenad Tomasev; Shekoofeh Azizi; Karan Singhal; et al. (CoRR, 2024)

Capabilities of Gemini Models in Medicine. - Khaled Saab 003; Tao Tu 001; Wei-Hung Weng; Ryutaro Tanno; David Stutz; Ellery Wulczyn; Fan Zhang; Tim Strother; Chunjong Park; Elahe Vedadi; Juanma Zambrano Chaves; Szu-Yeu Hu; et al. (CoRR, 2024)

NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. - 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 (CoRR, 2024)

Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning. - Kaiwen Wang; Rahul Kidambi; Ryan Sullivan; Alekh Agarwal; Christoph Dann; Andrea Michi; Marco Gelmi; Yunxuan Li; Raghav Gupta; Avinava Dubey; Alexandre Ramé; Johan Ferret; et al. (CoRR, 2024)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Yunxuan Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (J. Mach. Learn. Res., 2024)