Ren, Jie

52 publications

AAAI 2025 HS-FPN: High Frequency and Spatial Perception FPN for Tiny Object Detection Zican Shi, Jing Hu, Jie Ren, Hengkang Ye, Xuyang Yuan, Yan Ouyang, Jia He, Bo Ji, Junyu Guo

NeurIPS 2025 Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy Jie Ren, Zhenwei Dai, Xianfeng Tang, Yue Xing, Shenglai Zeng, Hui Liu, Jingying Zeng, Qiankun Peng, Samarth Varshney, Suhang Wang, Qi He, Charu C. Aggarwal, Hui Liu

AAAI 2025 Monitoring Primitive Interactions During the Training of DNNs Jie Ren, Xinhao Zheng, Jiyu Liu, Andrew Lizarraga, Ying Nian Wu, Liang Lin, Quanshi Zhang

ICLRW 2025 On the Cone Effect in the Learning Dynamics Zhanpeng Zhou, Yongyi Yang, Jie Ren, Mahito Sugiyama, Junchi Yan

IJCAI 2025 Optimizing Personalized Federated Learning Through Adaptive Layer-Wise Learning Weihang Chen, Cheng Yang, Jie Ren, Zhiqiang Li, Zheng Wang

NeurIPS 2025 Private Training Large-Scale Models with Efficient DP-SGD Liangyu Wang, Junxiao Wang, Jie Ren, Zihang Xiang, David E. Keyes, Di Wang

ICLR 2025 RRM: Robust Reward Model Training Mitigates Reward Hacking 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

ICLR 2025 Revisiting Mode Connectivity in Neural Networks with Bezier Surface Jie Ren, Pin-Yu Chen, Ren Wang

TMLR 2025 SETS: Leveraging Self-Verification and Self-Correction for Improved Test-Time Scaling Jiefeng Chen, Jie Ren, Xinyun Chen, Chengrun Yang, Ruoxi Sun, Jinsung Yoon, Sercan O Arik

CVPR 2025 Six-CD: Benchmarking Concept Removals for Text-to-Image Diffusion Models Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu

AISTATS 2025 Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear Regression Yingqian Cui, Jie Ren, Pengfei He, Hui Liu, Jiliang Tang, Yue Xing

NeurIPSW 2024 Comparing Human and LLM Ratings of Music-Recommendation Quality with User Context Sherol Chen, Yuri Vasilevski, Andrew Kyle Lampinen, Amnah Ahmad, Ndaba Ndebele, Sally Goldman, Michael Curtis Mozer, Jie Ren

NeurIPS 2024 Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model Yanpeng Ye, Jie Ren, Shaozhou Wang, Yuwei Wan, Imran Razzak, Bram Hoex, Haofeng Wang, Tong Xie, Wenjie Zhang

NeurIPSW 2024 Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model Yanpeng Ye, Jie Ren, Shaozhou Wang, Yuwei Wan, Yixuan Liu, Imran Razzak, Haofen Wang, Tong Xie, Wenjie Zhang

NeurIPSW 2024 FlashDP: Memory-Efficient and High-Throughput DP-SGD Training for Large Language Models Liangyu Wang, Junxiao Wang, Jie Ren, Zihang Xiang, David E. Keyes, Di Wang

WACV 2024 Neural Style Protection: Counteracting Unauthorized Neural Style Transfer Yaxin Li, Jie Ren, Han Xu, Hui Liu

ICLR 2024 Sharpness-Aware Data Poisoning Attack Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang

TMLR 2024 Stealthy Backdoor Attack via Confidence-Driven Sampling Pengfei He, Yue Xing, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou

ICMLW 2024 Universal Self-Consistency for Large Language Models Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, Denny Zhou

ECCV 2024 Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang

NeurIPSW 2024 ZO-Offloading: Fine-Tuning LLMs with 100 Billion Parameters on a Single GPU Liangyu Wang, Jie Ren, Hang Xu, Junxiao Wang, David E. Keyes, Di Wang

JMLR 2023 A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan

ICML 2023 A Simple Zero-Shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models James Urquhart Allingham, Jie Ren, Michael W Dusenberry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, Balaji Lakshminarayanan

ICLR 2023 Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN? Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang

CVPR 2023 Defining and Quantifying the Emergence of Sparse Concepts in DNNs Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang

AAAI 2023 DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian

CVPR 2023 Improving Zero-Shot Generalization and Robustness of Multi-Modal Models Yunhao Ge, Jie Ren, Andrew Gallagher, Yuxiao Wang, Ming-Hsuan Yang, Hartwig Adam, Laurent Itti, Balaji Lakshminarayanan, Jiaping Zhao

ICMLW 2023 Morse Neural Networks for Uncertainty Quantification Benoit Dherin, Huiyi Hu, Jie Ren, Michael W Dusenberry, Balaji Lakshminarayanan

ICLR 2023 Out-of-Distribution Detection and Selective Generation for Conditional Language Models Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh, Balaji Lakshminarayanan, Peter J Liu

ICML 2023 Probabilistic Categorical Adversarial Attack and Adversarial Training Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu, Hui Liu, Jiliang Tang

NeurIPSW 2023 Self-Evaluation Improves Selective Generation in Large Language Models Jie Ren, Yao Zhao, Tu Vu, Peter J Liu, Balaji Lakshminarayanan

MLOSS 2023 TorchOpt: An Efficient Library for Differentiable Optimization Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang

ICLR 2023 Transferable Unlearnable Examples Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang

NeurIPS 2022 A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning Bo Liu, Xidong Feng, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang

NeurIPSW 2022 Improving Zero-Shot Generalization and Robustness of Multi-Modal Models Yunhao Ge, Jie Ren, Ming-Hsuan Yang, Yuxiao Wang, Andrew Gallagher, Hartwig Adam, Laurent Itti, Balaji Lakshminarayanan, Jiaping Zhao

NeurIPSW 2022 Improving the Robustness of Conditional Language Models by Detecting and Removing Input Noise Kundan Krishna, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J Liu

ECCV 2022 MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment Jie Ren, Wenteng Liang, Ran Yan, Luo Mai, Shiwen Liu, Xiao Liu

NeurIPSW 2022 Out-of-Distribution Detection and Selective Generation for Conditional Language Models Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh, Balaji Lakshminarayanan, Peter J Liu

ICMLW 2022 Plex: Towards Reliability Using Pretrained Large Model Extensions Dustin Tran, Jeremiah Zhe Liu, Michael W Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda E Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, E. Kelly Buchanan, Kevin Patrick Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

NeurIPS 2022 Pluralistic Image Completion with Gaussian Mixture Models Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu

NeurIPSW 2022 Reliability Benchmarks for Image Segmentation E. Kelly Buchanan, Michael W Dusenberry, Jie Ren, Kevin Patrick Murphy, Balaji Lakshminarayanan, Dustin Tran

NeurIPSW 2022 TorchOpt: An Efficient Library for Differentiable Optimization Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang

ICML 2022 Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs Jie Ren, Mingjie Li, Meng Zhou, Shih-Han Chan, Quanshi Zhang

ICLR 2021 A Unified Approach to Interpreting and Boosting Adversarial Transferability Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang

NeurIPS 2021 Exploring the Limits of Out-of-Distribution Detection Stanislav Fort, Jie Ren, Balaji Lakshminarayanan

ICML 2021 Interpreting and Disentangling Feature Components of Various Complexity from DNNs Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang

ICML 2021 Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network Zhibin Duan, Dongsheng Wang, Bo Chen, Chaojie Wang, Wenchao Chen, Yewen Li, Jie Ren, Mingyuan Zhou

NeurIPS 2021 Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang

NeurIPS 2020 HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory Jie Ren, Minjia Zhang, Dong Li

ICLR 2020 Interpretable Complex-Valued Neural Networks for Privacy Protection Liyao Xiang, Haotian Ma, Hao Zhang, Yifan Zhang, Jie Ren, Quanshi Zhang

NeurIPS 2019 Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D. Sculley, Sebastian Nowozin, Joshua Dillon, Balaji Lakshminarayanan, Jasper Snoek

NeurIPS 2019 Likelihood Ratios for Out-of-Distribution Detection Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark Depristo, Joshua Dillon, Balaji Lakshminarayanan