Jie Ren - RankMe

43 papers A* 7B 1Journal 32Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	RRM: Robust Reward Model Training Mitigates Reward Hacking. ICLR Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasia Makarova, Jeremiah Zhe Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh
2024	J	`jnl`	RRM: Robust Reward Model Training Mitigates Reward Hacking. CoRR Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasiia Makarova, Jeremiah Z. Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh
2023	J	`jnl`	A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. J. Mach. Learn. Res. Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
2023	A*	`conf`	A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models. ICML James Urquhart Allingham, Jie Ren, Michael W. Dusenberry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, Balaji Lakshminarayanan
2023	J	`jnl`	A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models. CoRR James Urquhart Allingham, Jie Ren, Michael W. Dusenberry, Jeremiah Zhe Liu, Xiuye Gu, Yin Cui, Dustin Tran, Balaji Lakshminarayanan
2023	J	`jnl`	Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models. CoRR Yunhao Ge, Jie Ren, Jiaping Zhao, Kaifeng Chen, Andrew Gallagher, Laurent Itti, Balaji Lakshminarayanan
2023	A*	`conf`	Improving Zero-shot Generalization and Robustness of Multi-Modal Models. CVPR Yunhao Ge, Jie Ren, Andrew Gallagher, Yuxiao Wang, Ming-Hsuan Yang, Hartwig Adam, Laurent Itti, Balaji Lakshminarayanan, Jiaping Zhao
2023	—	`conf`	Improving the Robustness of Summarization Models by Detecting and Removing Input Noise. EMNLP (Findings) Kundan Krishna, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J. Liu
2023	J	`jnl`	Morse Neural Networks for Uncertainty Quantification. CoRR Benoit Dherin, Huiyi Hu, Jie Ren, Michael W. Dusenberry, Balaji Lakshminarayanan
2023	—	`conf`	On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study. EMNLP (Findings) Polina Zablotskaia, Du Phan, Joshua Maynez, Shashi Narayan, Jie Ren, Jeremiah Z. Liu
2023	J	`jnl`	On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study. CoRR Polina Zablotskaia, Du Phan, Joshua Maynez, Shashi Narayan, Jie Ren, Jeremiah Z. Liu
2023	A*	`conf`	Out-of-Distribution Detection and Selective Generation for Conditional Language Models. ICLR Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh, Balaji Lakshminarayanan, Peter J. Liu
2023	—	`conf`	Self-Evaluation Improves Selective Generation in Large Language Models. ICBINB Jie Ren, Yao Zhao, Tu Vu, Peter J. Liu, Balaji Lakshminarayanan
2023	J	`jnl`	Self-Evaluation Improves Selective Generation in Large Language Models. CoRR Jie Ren, Yao Zhao, Tu Vu, Peter J. Liu, Balaji Lakshminarayanan
2022	J	`jnl`	A New Context Tree Inference Algorithm for Variable Length Markov Chain Model with Applications to Biological Sequence Analyses. J. Comput. Biol. Shaokun An, Jie Ren, Fengzhu Sun, Lin Wan
2022	J	`jnl`	A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. CoRR Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zack Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
2022	J	`jnl`	Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions. Medical Image Anal. Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zachary Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Gregory S. Corrado, Umesh Telang, Yun Liu, A. Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens
2022	J	`jnl`	Improving Zero-shot Generalization and Robustness of Multi-modal Models. CoRR Yunhao Ge, Jie Ren, Yuxiao Wang, Andrew Gallagher, Ming-Hsuan Yang, Laurent Itti, Hartwig Adam, Balaji Lakshminarayanan, Jiaping Zhao
2022	J	`jnl`	Improving the Robustness of Summarization Models by Detecting and Removing Input Noise. CoRR Kundan Krishna, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J. Liu
2022	J	`jnl`	Out-of-Distribution Detection and Selective Generation for Conditional Language Models. CoRR Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh, Balaji Lakshminarayanan, Peter J. Liu
2022	J	`jnl`	Plex: Towards Reliability using Pretrained Large Model Extensions. CoRR Dustin Tran, Jeremiah Z. Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan
2021	J	`jnl`	A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection. CoRR Jie Ren, Stanislav Fort, Jeremiah Z. Liu, Abhijit Guha Roy, Shreyas Padhy, Balaji Lakshminarayanan
2021	J	`jnl`	Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions. CoRR Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zachary Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Gregory S. Corrado, Umesh Telang, Yun Liu, A. Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens
2021	A*	`conf`	Exploring the Limits of Out-of-Distribution Detection. NeurIPS Stanislav Fort, Jie Ren, Balaji Lakshminarayanan
2021	J	`jnl`	Exploring the Limits of Out-of-Distribution Detection. CoRR Stanislav Fort, Jie Ren, Balaji Lakshminarayanan
2021	J	`jnl`	KIMI: Knockoff Inference for Motif Identification from molecular sequences with controlled false discovery rate. Bioinform. Xin Bai, Jie Ren, Yingying Fan, Fengzhu Sun
2021	J	`jnl`	Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran
2020	J	`jnl`	Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data. Quant. Biol. Lin Wan, Xin Kang, Jie Ren, Fengzhu Sun
2020	J	`jnl`	Identifying viruses from metagenomic data using deep learning. Quant. Biol. Jie Ren, Kai Song, Chao Deng, Nathan A. Ahlgren, Jed A. Fuhrman, Yi Li, Xiaohui Xie, Ryan Poplin, Fengzhu Sun
2020	J	`jnl`	Predicting the Number of Bases to Attain Sufficient Coverage in High-Throughput Sequencing Experiments. J. Comput. Biol. Chao Deng, Timothy Daley, Peter Calabrese, Jie Ren, Andrew D. Smith
2020	J	`jnl`	Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks. CoRR Shreyas Padhy, Zachary Nado, Jie Ren, Jeremiah Z. Liu, Jasper Snoek, Balaji Lakshminarayanan
2019	J	`jnl`	Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift. CoRR Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek
2019	A*	`conf`	Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift. NeurIPS Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado
2019	A*	`conf`	Likelihood Ratios for Out-of-Distribution Detection. NeurIPS Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
2019	J	`jnl`	Likelihood Ratios for Out-of-Distribution Detection. CoRR Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
2019	J	`jnl`	SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders. CoRR Peter J. Liu, Yu-An Chung, Jie Ren
2017	J	`jnl`	CAFE: aCcelerated Alignment-FrEe sequence analysis. Nucleic Acids Res. Yang Young Lu, Kujin Tang, Jie Ren, Jed A. Fuhrman, Michael S. Waterman, Fengzhu Sun
2017	J	`jnl`	Prediction of virus-host infectious association by supervised learning methods. BMC Bioinform. Mengge Zhang, Lianping Yang, Jie Ren, Nathan A. Ahlgren, Jed A. Fuhrman, Fengzhu Sun
2016	J	`jnl`	Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics. Bioinform. Jie Ren, Kai Song, Minghua Deng, Gesine Reinert, Charles H. Cannon, Fengzhu Sun
2014	J	`jnl`	New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing. Briefings Bioinform. Kai Song, Jie Ren, Gesine Reinert, Minghua Deng, Michael S. Waterman, Fengzhu Sun
2013	J	`jnl`	Alignment-Free Sequence Comparison Based on Next-Generation Sequencing Reads. J. Comput. Biol. Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng, Fengzhu Sun
2013	J	`jnl`	Multiple alignment-free sequence comparison. Bioinform. Jie Ren, Kai Song, Fengzhu Sun, Minghua Deng, Gesine Reinert
2012	B	`conf`	Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads: Extended Abstract. RECOMB Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng, Fengzhu Sun