Nan Du - RankMe

69 papers A* 19A 2B 1Misc 1Journal 36Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Parallel Track Transformers: Enabling Fast GPU Inference with Reduced Synchronization. CoRR Chong Wang, Nan Du, Tom Gunter, Tao Lei, Kulin Seth, Senyu Tong, Jianyu Wang, Guoli Yin, Xiyou Zhou, Kelvin Zou, Ruoming Pang
2025	J	`jnl`	AXLearn: Modular Large Model Training on Heterogeneous Infrastructure. CoRR Mark Lee, Tom Gunter, Chang Lan, John Peebles, Hanzhi Zhou, Kelvin Zou, Sneha Bangalore, Chung-Cheng Chiu, Nan Du, Xianzhi Du, Philipp Dufter, Ruixuan Hou, Haoshuo Huang, Dongseong Hwang, Xiang Kong, Jinhao Lei, Tao Lei, Meng Li, Li Li, Jiarui Lu, Zhiyun Lu, Yiping Ma, David Qiu, Vivek Rathod, Senyu Tong, Zhucheng Tu, Jianyu Wang, Yongqiang Wang, Zirui Wang, Floris Weers, Sam Wiseman, Guoli Yin, Bowen Zhang, Xiyou Zhou, Danyang Zhuo, Cheng Leong, Ruoming Pang
2025	A*	`conf`	EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing. ICLR Haotian Sun, Tao Lei, Bowen Zhang, Yanghao Li, Haoshuo Huang, Ruoming Pang, Bo Dai, Nan Du
2025	A*	`conf`	Instruction-Following Pruning for Large Language Models. ICML Bairu Hou, Qibin Chen, Jianyu Wang, Guoli Yin, Chong Wang, Nan Du, Ruoming Pang, Shiyu Chang, Tao Lei
2025	J	`jnl`	Instruction-Following Pruning for Large Language Models. CoRR Bairu Hou, Qibin Chen, Jianyu Wang, Guoli Yin, Chong Wang, Nan Du, Ruoming Pang, Shiyu Chang, Tao Lei
2024	J	`jnl`	Deep State-Space Generative Model For Correlated Time-to-Event Predictions. CoRR Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui
2024	J	`jnl`	EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing. CoRR Haotian Sun, Tao Lei, Bowen Zhang, Yanghao Li, Haoshuo Huang, Ruoming Pang, Bo Dai, Nan Du
2024	J	`jnl`	Knowledge Graph Reasoning with Self-supervised Reinforcement Learning. CoRR Ying Ma, Owen Burns, Mingqiu Wang, Gang Li, Nan Du, Laurent El Shafey, Liqiang Wang, Izhak Shafran, Hagen Soltau
2024	J	`jnl`	Learning to Select the Best Forecasting Tasks for Clinical Outcome Prediction. CoRR Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M. Dai
2024	J	`jnl`	MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training. CoRR Brandon McKinzie, Zhe Gan, Jean-Philippe Fauconnier, Sam Dodge, Bowen Zhang, Philipp Dufter, Dhruti Shah, Xianzhi Du, Futang Peng, Floris Weers, Anton Belyi, Haotian Zhang, Karanjeet Singh, Doug Kang, Ankur Jain, Hongyu Hè, Max Schwarzer, Tom Gunter, Xiang Kong, Aonan Zhang, Jianyu Wang, Chong Wang, Nan Du, Tao Lei, Sam Wiseman, Guoli Yin, Mark Lee, Zirui Wang, Ruoming Pang, Peter Grasch, Alexander Toshev, Yinfei Yang
2024	—	`conf`	MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training. ECCV (29) Brandon McKinzie, Zhe Gan, Jean-Philippe Fauconnier, Sam Dodge, Bowen Zhang, Philipp Dufter, Dhruti Shah, Xianzhi Du, Futang Peng, Anton Belyi, Haotian Zhang, Karanjeet Singh, Doug Kang, Hongyu Hè, Max Schwarzer, Tom Gunter, Xiang Kong, Aonan Zhang, Jianyu Wang, Chong Wang, Nan Du, Tao Lei, Sam Wiseman, Mark Lee, Zirui Wang, Ruoming Pang, Peter Grasch, Alexander Toshev, Yinfei Yang
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
2023	A*	`conf`	Brainformers: Trading Simplicity for Efficiency. ICML Yanqi Zhou, Nan Du, Yanping Huang, Daiyi Peng, Chang Lan, Da Huang, Siamak Shakeri, David R. So, Andrew M. Dai, Yifeng Lu, Zhifeng Chen, Quoc V. Le, Claire Cui, James Laudon, Jeff Dean
2023	J	`jnl`	Brainformers: Trading Simplicity for Efficiency. CoRR Yanqi Zhou, Nan Du, Yanping Huang, Daiyi Peng, Chang Lan, Da Huang, Siamak Shakeri, David R. So, Andrew M. Dai, Yifeng Lu, Zhifeng Chen, Quoc V. Le, Claire Cui, James Laudon, Jeff Dean
2023	A*	`conf`	Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference. NeurIPS Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du, Vincent Y. Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang
2023	J	`jnl`	Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference. CoRR Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie, Kenton Lee, Yanqi Zhou, Nan Du, Vincent Y. Zhao, Yuexin Wu, Bo Li, Yu Zhang, Ming-Wei Chang
2023	A*	`conf`	DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. NeurIPS Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu
2023	J	`jnl`	DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. CoRR Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu
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`	Learning to Skip for Language Modeling. CoRR Dewen Zeng, Nan Du, Tao Wang, Yuanzhong Xu, Tao Lei, Zhifeng Chen, Claire Cui
2023	A*	`conf`	Lifelong Language Pretraining with Distribution-Specialized Experts. ICML Wuyang Chen, Yanqi Zhou, Nan Du, Yanping Huang, James Laudon, Zhifeng Chen, Claire Cui
2023	J	`jnl`	Lifelong Language Pretraining with Distribution-Specialized Experts. CoRR Wuyang Chen, Yanqi Zhou, Nan Du, Yanping Huang, James Laudon, Zhifeng Chen, Claire Cui
2023	Misc	`conf`	Massively Multilingual Shallow Fusion with Large Language Models. ICASSP Ke Hu, Tara N. Sainath, Bo Li, Nan Du, Yanping Huang, Andrew M. Dai, Yu Zhang, Rodrigo Cabrera, Zhifeng Chen, Trevor Strohman
2023	J	`jnl`	Massively Multilingual Shallow Fusion with Large Language Models. CoRR Ke Hu, Tara N. Sainath, Bo Li, Nan Du, Yanping Huang, Andrew M. Dai, Yu Zhang, Rodrigo Cabrera, Zhifeng Chen, Trevor Strohman
2023	J	`jnl`	PaLM 2 Technical Report. CoRR Rohan Anil, Andrew M. Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H. Clark, Laurent El Shafey, Yanping Huang, Kathy Meier-Hellstern, Gaurav Mishra, Erica Moreira, Mark Omernick, Kevin Robinson, Sebastian Ruder, Yi Tay, Kefan Xiao, Yuanzhong Xu, Yujing Zhang, Gustavo Hernández Ábrego, Junwhan Ahn, Jacob Austin, Paul Barham, Jan A. Botha, James Bradbury, Siddhartha Brahma, Kevin Brooks, Michele Catasta, Yong Cheng, Colin Cherry, Christopher A. Choquette-Choo, Aakanksha Chowdhery, Clément Crepy, Shachi Dave, Mostafa Dehghani, Sunipa Dev, Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vladimir Feinberg, Fangxiaoyu Feng, Vlad Fienber, Markus Freitag, Xavier Garcia, Sebastian Gehrmann, Lucas Gonzalez, et al.
2023	J	`jnl`	PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel
2023	A*	`conf`	ReAct: Synergizing Reasoning and Acting in Language Models. ICLR Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R. Narasimhan, Yuan Cao
2022	J	`jnl`	Designing Effective Sparse Expert Models. CoRR Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, William Fedus
2022	A*	`conf`	Finetuned Language Models are Zero-Shot Learners. ICLR Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le
2022	A*	`conf`	GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. ICML Nan Du, Yanping Huang, Andrew M. Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten P. Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathleen S. Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui
2022	A*	`conf`	Mixture-of-Experts with Expert Choice Routing. NeurIPS Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Y. Zhao, Andrew M. Dai, Zhifeng Chen, Quoc V. Le, James Laudon
2022	J	`jnl`	Mixture-of-Experts with Expert Choice Routing. CoRR Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Y. Zhao, Andrew M. Dai, Zhifeng Chen, Quoc Le, James Laudon
2022	J	`jnl`	PaLM: Scaling Language Modeling with Pathways. CoRR Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel
2022	J	`jnl`	ReAct: Synergizing Reasoning and Acting in Language Models. CoRR Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, Yuan Cao
2021	J	`jnl`	Finetuned Language Models Are Zero-Shot Learners. CoRR Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le
2021	J	`jnl`	GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. CoRR Nan Du, Yanping Huang, Andrew M. Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathy Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui
2021	J	`jnl`	R2D2: Relational Text Decoding with Transformers. CoRR Aryan Arbabi, Mingqiu Wang, Laurent El Shafey, Nan Du, Izhak Shafran
2020	A*	`conf`	Deep State-Space Generative Model For Correlated Time-to-Event Predictions. KDD Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui
2020	A*	`conf`	Learning to Select Best Forecast Tasks for Clinical Outcome Prediction. NeurIPS Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M. Dai
2020	B	`conf`	The Medical Scribe: Corpus Development and Model Performance Analyses. LREC Izhak Shafran, Nan Du, Linh Tran, Amanda Perry, Lauren Keyes, Mark Knichel, Ashley Domin, Lei Huang, Yuhui Chen, Gang Li, Mingqiu Wang, Laurent El Shafey, Hagen Soltau, Justin S. Paul
2020	J	`jnl`	The Medical Scribe: Corpus Development and Model Performance Analyses. CoRR Izhak Shafran, Nan Du, Linh Tran, Amanda Perry, Lauren Keyes, Mark Knichel, Ashley Domin, Lei Huang, Yuhui Chen, Gang Li, Mingqiu Wang, Laurent El Shafey, Hagen Soltau, Justin S. Paul
2019	J	`jnl`	Deep Physiological State Space Model for Clinical Forecasting. CoRR Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui
2019	—	`conf`	Extracting Symptoms and their Status from Clinical Conversations. ACL (1) Nan Du, Kai Chen, Anjuli Kannan, Linh Tran, Yuhui Chen, Izhak Shafran
2019	J	`jnl`	Extracting Symptoms and their Status from Clinical Conversations. CoRR Nan Du, Kai Chen, Anjuli Kannan, Linh Tran, Yuhui Chen, Izhak Shafran
2019	—	`conf`	Learning to Infer Entities, Properties and their Relations from Clinical Conversations. EMNLP/IJCNLP (1) Nan Du, Mingqiu Wang, Linh Tran, Gang Lee, Izhak Shafran
2019	J	`jnl`	Learning to Infer Entities, Properties and their Relations from Clinical Conversations. CoRR Nan Du, Mingqiu Wang, Linh Tran, Gang Li, Izhak Shafran
2018	A*	`conf`	Learning Temporal Point Processes via Reinforcement Learning. NeurIPS Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song
2018	J	`jnl`	Learning Temporal Point Processes via Reinforcement Learning. CoRR Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song
2017	J	`jnl`	Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. J. Mach. Learn. Res. Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song
2016	—	`conf`	Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions. NIPS Yichen Wang, Nan Du, Rakshit S. Trivedi, Le Song
2016	J	`jnl`	Influence Estimation and Maximization in Continuous-Time Diffusion Networks. ACM Trans. Inf. Syst. Manuel Gomez-Rodriguez, Le Song, Nan Du, Hongyuan Zha, Bernhard Schölkopf
2016	A*	`conf`	Isotonic Hawkes Processes. ICML Yichen Wang, Bo Xie, Nan Du, Le Song
2016	—	`—`	Modeling, learning, and inference of high-dimensional asynchronous event data. Nan Du
2016	A*	`conf`	Recurrent Marked Temporal Point Processes: Embedding Event History to Vector. KDD Nan Du, Hanjun Dai, Rakshit S. Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, Le Song
2016	J	`jnl`	Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. CoRR Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song
2015	A	`conf`	Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades. AISTATS Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Mohammad Zamani, Nan Du, Hongyuan Zha, Le Song
2015	J	`jnl`	Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades. CoRR Mehrdad Farajtabar, Manuel Gomez-Rodriguez, Nan Du, Mohammad Zamani, Hongyuan Zha, Le Song
2015	A*	`conf`	Constructing Disease Network and Temporal Progression Model via Context-Sensitive Hawkes Process. ICDM Edward Choi, Nan Du, Robert Chen, Le Song, Jimeng Sun
2015	A*	`conf`	Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams. KDD Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J. Smola, Le Song
2015	—	`conf`	Time-Sensitive Recommendation From Recurrent User Activities. NIPS Nan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song
2014	A*	`conf`	Influence Function Learning in Information Diffusion Networks. ICML Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song
2014	—	`conf`	Learning Time-Varying Coverage Functions. NIPS Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song
2014	—	`conf`	Shaping Social Activity by Incentivizing Users. NIPS Mehrdad Farajtabar, Nan Du, Manuel Gomez-Rodriguez, Isabel Valera, Hongyuan Zha, Le Song
2014	J	`jnl`	Shaping Social Activity by Incentivizing Users. CoRR Mehrdad Farajtabar, Nan Du, Manuel Gomez-Rodriguez, Isabel Valera, Hongyuan Zha, Le Song
2013	J	`jnl`	Continuous-Time Influence Maximization for Multiple Items. CoRR Nan Du, Yingyu Liang, Maria-Florina Balcan, Le Song
2013	—	`conf`	Scalable Influence Estimation in Continuous-Time Diffusion Networks. NIPS Nan Du, Le Song, Manuel Gomez-Rodriguez, Hongyuan Zha
2013	J	`jnl`	Scalable Influence Estimation in Continuous-Time Diffusion Networks. CoRR Nan Du, Le Song, Manuel Gomez-Rodriguez, Hongyuan Zha
2013	A	`conf`	Uncover Topic-Sensitive Information Diffusion Networks. AISTATS Nan Du, Le Song, Hyenkyun Woo, Hongyuan Zha
2012	—	`conf`	Learning Networks of Heterogeneous Influence. NIPS Nan Du, Le Song, Alexander J. Smola, Ming Yuan