Jin, Ming

49 publications

ICLR 2025 A Black Swan Hypothesis: The Role of Human Irrationality in AI Safety Hyunin Lee, Chanwoo Park, David Abel, Ming Jin

L4DC 2025 A Dynamic Penalization Framework for Online Rank-1 Semidefinite Programming Relaxations Ahmad Al-Tawaha, Javad Lavaei, Ming Jin

NeurIPS 2025 Can LLMs Correct Themselves? a Benchmark of Self-Correction in LLMs Guiyao Tie, Zenghui Yuan, Zeli Zhao, Chaoran Hu, Tianhe Gu, Ruihang Zhang, Sizhe Zhang, Junran Wu, Xiaoyue Tu, Ming Jin, Qingsong Wen, Lixing Chen, Pan Zhou, Lichao Sun

NeurIPS 2025 Don’t Trade Off Safety: Diffusion Regularization for Constrained Offline RL Junyu Guo, Zhi Zheng, Donghao Ying, Ming Jin, Shangding Gu, Costas Spanos, Javad Lavaei

NeurIPS 2025 DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs Dongyuan Li, Shiyin Tan, Ying Zhang, Ming Jin, Shirui Pan, Manabu Okumura, Renhe Jiang

ECML-PKDD 2025 Improving Novel Anomaly Detection with Domain-Invariant Latent Representations Padmaksha Roy, Ming Jin, Himanshu Singhal, Tyler Cody, Kevin Choi

ICML 2025 Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning Mahavir Dabas, Si Chen, Charles Fleming, Ming Jin, Ruoxi Jia

ICLR 2025 LLMs Can Plan Only if We Tell Them Bilgehan Sel, Ruoxi Jia, Ming Jin

ICML 2025 LLMs Can Reason Faster Only if We Let Them Bilgehan Sel, Lifu Huang, Naren Ramakrishnan, Ruoxi Jia, Ming Jin

NeurIPS 2025 Multi-Scale Finetuning for Encoder-Based Time Series Foundation Models Zhongzheng Qiao, Chenghao Liu, Yiming Zhang, Ming Jin, Quang Pham, Qingsong Wen, Ponnuthurai Nagaratnam Suganthan, Xudong Jiang, Savitha Ramasamy

ICML 2025 Position: AI Safety Must Embrace an Antifragile Perspective Ming Jin, Hyunin Lee

NeurIPS 2025 Probing Hidden Knowledge Holes in Unlearned LLMs Myeongseob Ko, Hoang Anh Just, Charles Fleming, Ming Jin, Ruoxi Jia

NeurIPS 2025 Reinforcement Learning with Backtracking Feedback Bilgehan Sel, Vaishakh Keshava, Phillip Wallis, Lukas Rutishauser, Ming Jin, Dingcheng Li

ICLR 2025 Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning Shangding Gu, Laixi Shi, Muning Wen, Ming Jin, Eric Mazumdar, Yuejie Chi, Adam Wierman, Costas Spanos

NeurIPS 2025 ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models Bosong Huang, Ming Jin, Yuxuan Liang, Johan Barthelemy, Debo Cheng, Qingsong Wen, Chenghao Liu, Shirui Pan

IJCAI 2025 T2S: High-Resolution Time Series Generation with Text-to-Series Diffusion Models Yunfeng Ge, Jiawei Li, Yiji Zhao, Haomin Wen, Zhao Li, Meikang Qiu, Hongyan Li, Ming Jin, Shirui Pan

ICLR 2025 Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts Xiaoming Shi, Shiyu Wang, Yuqi Nie, Dianqi Li, Zhou Ye, Qingsong Wen, Ming Jin

ICML 2025 Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Siru Zhong, Weilin Ruan, Ming Jin, Huan Li, Qingsong Wen, Yuxuan Liang

ICLR 2025 TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis Shiyu Wang, Jiawei Li, Xiaoming Shi, Zhou Ye, Baichuan Mo, Wenze Lin, Ju Shengtong, Zhixuan Chu, Ming Jin

ICLR 2025 Towards Neural Scaling Laws for Time Series Foundation Models Qingren Yao, Chao-Han Huck Yang, Renhe Jiang, Yuxuan Liang, Ming Jin, Shirui Pan

ICML 2024 Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models Bilgehan Sel, Ahmad Tawaha, Vanshaj Khattar, Ruoxi Jia, Ming Jin

NeurIPS 2024 Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective Jiaxi Hu, Yuehong Hu, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang

AAAI 2024 Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Ming Jin, Alois Knoll

NeurIPS 2024 Boosting Alignment for Post-Unlearning Text-to-Image Generative Models Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker, Jiachen T. Wang, Qinbin Li, Ming Jin, Dawn Song, Ruoxi Jia

TMLR 2024 Data-Centric Defense: Shaping Loss Landscape with Augmentations to Counter Model Inversion Si Chen, Feiyang Kang, Nikhil Abhyankar, Ming Jin, Ruoxi Jia

NeurIPS 2024 Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas Spanos, Adam Wierman, Ming Jin

NeurIPS 2024 Fairness-Aware Meta-Learning via Nash Bargaining Yi Zeng, Xuelin Yang, Li Chen, Cristian Canton Ferrer, Ming Jin, Michael I. Jordan, Ruoxi Jia

ICML 2024 Pausing Policy Learning in Non-Stationary Reinforcement Learning Hyunin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi

ICML 2024 Position: What Can Large Language Models Tell Us About Time Series Analysis Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, Qingsong Wen

NeurIPSW 2024 Scaling to Billion Parameters for Time Series Foundation Models with Mixture of Experts Xiaoming Shi, Shiyu Wang, Yuqi Nie, Dianqi Li, Zhou Ye, Qingsong Wen, Ming Jin

TMLR 2024 TeaMs-RL: Teaching LLMs to Generate Better Instruction Datasets via Reinforcement Learning Shangding Gu, Alois Knoll, Ming Jin

CVPR 2024 The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes Myeongseob Ko, Feiyang Kang, Weiyan Shi, Ming Jin, Zhou Yu, Ruoxi Jia

ICLR 2024 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, Qingsong Wen

ICLR 2023 A CMDP-Within-Online Framework for Meta-Safe Reinforcement Learning Vanshaj Khattar, Yuhao Ding, Bilgehan Sel, Javad Lavaei, Ming Jin

ICLR 2023 LAVA: Data Valuation Without Pre-Specified Learning Algorithms Hoang Anh Just, Feiyang Kang, Tianhao Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia

L4DC 2023 Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold Bilgehan Sel, Ahmad Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, Ming Jin

AAAI 2023 Non-Stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design Yuhao Ding, Ming Jin, Javad Lavaei

AAAI 2023 On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds Ming Jin, Vanshaj Khattar, Harshal Kaushik, Bilgehan Sel, Ruoxi Jia

ICCV 2023 Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study Myeongseob Ko, Ming Jin, Chenguang Wang, Ruoxi Jia

NeurIPS 2023 Tempo Adaptation in Non-Stationary Reinforcement Learning Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi

ICLR 2023 Towards Robustness Certification Against Universal Perturbations Yi Zeng, Zhouxing Shi, Ming Jin, Feiyang Kang, Lingjuan Lyu, Cho-Jui Hsieh, Ruoxi Jia

AAAI 2023 Winning the CityLearn Challenge: Adaptive Optimization with Evolutionary Search Under Trajectory-Based Guidance Vanshaj Khattar, Ming Jin

ICLR 2022 Adversarial Unlearning of Backdoors via Implicit Hypergradient Yi Zeng, Si Chen, Won Park, Zhuoqing Mao, Ming Jin, Ruoxi Jia

NeurIPS 2022 Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs Ming Jin, Yuan-Fang Li, Shirui Pan

AAAI 2022 Recurrent Neural Network Controllers Synthesis with Stability Guarantees for Partially Observed Systems Fangda Gu, He Yin, Laurent El Ghaoui, Murat Arcak, Peter J. Seiler, Ming Jin

IJCAI 2021 Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning Ming Jin, Yizhen Zheng, Yuan-Fang Li, Chen Gong, Chuan Zhou, Shirui Pan

AAAI 2021 Power up! Robust Graph Convolutional Network via Graph Powering Ming Jin, Heng Chang, Wenwu Zhu, Somayeh Sojoudi

UAI 2017 Inverse Reinforcement Learning via Deep Gaussian Process Ming Jin, Andreas C. Damianou, Pieter Abbeel, Costas J. Spanos

CVPR 2007 A Real-Time ProCam System for Interaction with Chinese Ink-and-Wash Cartoons Ming Jin, Hui Zhang, Xubo Yang, Shuangjiu Xiao