Hu, Bin

36 publications

ICML 2025 Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching Aaron J Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen

ICLRW 2025 Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching Aaron J Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen

ICLR 2025 DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models Chengke Zou, Xingang Guo, Rui Yang, Junyu Zhang, Bin Hu, Huan Zhang

IJCAI 2025 External Memory Matters: Generalizable Object-Action Memory for Retrieval-Augmented Long-Term Video Understanding Jisheng Dang, Huicheng Zheng, Xudong Wu, Jingmei Jiao, Bimei Wang, Jun Yang, Bin Hu, Jianhuang Lai, Tat-Seng Chua

L4DC 2025 Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems Haoyu Li, Xiangru Zhong, Bin Hu, Huan Zhang

AAAI 2025 PhysDiff: Physiology-Based Dynamicity Disentangled Diffusion Model for Remote Physiological Measurement Wei Qian, Gaoji Su, Dan Guo, Jinxing Zhou, Xiaobai Li, Bin Hu, Shengeng Tang, Meng Wang

NeurIPS 2025 Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs Xingang Guo, Yaxin Li, XiangYi Kong, Yilan Jiang, Xiayu Zhao, Zhihua Gong, Yufan Zhang, Daixuan Li, Tianle Sang, Beixiao Zhu, Gregory Jun, Yingbing Huang, Yiqi Liu, Yuqi Xue, Rahul Dev Kundu, Qi Jian Lim, Yizhou Zhao, Luke Alexander Granger, Mohamed Badr Younis, Darioush Keivan, Nippun Sabharwal, Shreyanka Sinha, Prakhar Agarwal, Kojo Vandyck, Hanlin Mai, Zichen Wang, Aditya Venkatesh, Ayush Barik, Jiankun Yang, Chongying Yue, Jingjie He, Libin Wang, Licheng Xu, Hao Chen, Jinwen Wang, Liujun Xu, Rushabh Shetty, Ziheng Guo, Dahui Song, Manvi Jha, Weijie Liang, Weiman Yan, Bryan Zhang, Sahil Bhandary Karnoor, Jialiang Zhang, Rutva Pandya, Xinyi Gong, Mithesh Ballae Ganesh, Feize Shi, Ruiling Xu, Yifan Zhang, Yanfeng Ouyang, Lianhui Qin, Elyse Rosenbaum, Corey Snyder, Peter Seiler, Geir Dullerud, Xiaojia Shelly Zhang, Zuofu Cheng, Pavan Kumar Hanumolu, Jian Huang, Mayank Kulkarni, Mahdi Namazifar, Huan Zhang, Bin Hu

NeurIPS 2025 Two‑Stage Learning of Stabilizing Neural Controllers via Zubov Sampling and Iterative Domain Expansion Haoyu Li, Xiangru Zhong, Bin Hu, Huan Zhang

ICML 2024 COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability Xingang Guo, Fangxu Yu, Huan Zhang, Lianhui Qin, Bin Hu

ICLRW 2024 Confidence Calibration and Rationalization for LLMs via Multi-Agent Deliberation Ruixin Yang, Dheeraj Rajagopal, Shirley Anugrah Hayati, Bin Hu, Dongyeop Kang

ICML 2024 Fine-Grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention Aaron J Havens, Alexandre Araujo, Huan Zhang, Bin Hu

AAAI 2024 Focus Stacking with High Fidelity and Superior Visual Effects Bo Liu, Bin Hu, Xiuli Bi, Weisheng Li, Bin Xiao

IJCAI 2024 Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents Zihao Zhou, Bin Hu, Chenyang Zhao, Pu Zhang, Bin Liu

ICLR 2024 Novel Quadratic Constraints for Extending LipSDP Beyond Slope-Restricted Activations Patricia Pauli, Aaron J Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu

ICLR 2024 On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks Zi Wang, Bin Hu, Aaron J Havens, Alexandre Araujo, Yang Zheng, Yudong Chen, Somesh Jha

AAAI 2024 Structural Information Enhanced Graph Representation for Link Prediction Lei Shi, Bin Hu, Deng Zhao, Jianshan He, Zhiqiang Zhang, Jun Zhou

ICLR 2023 A Unified Algebraic Perspective on Lipschitz Neural Networks Alexandre Araujo, Aaron J Havens, Blaise Delattre, Alexandre Allauzen, Bin Hu

NeurIPS 2023 Complexity of Derivative-Free Policy Optimization for Structured $\mathcal{H}_\infty$ Control Xingang Guo, Darioush Keivan, Geir Dullerud, Peter Seiler, Bin Hu

NeurIPS 2023 Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability Haotian Xue, Alexandre Araujo, Bin Hu, Yongxin Chen

NeurIPS 2023 Exploiting Connections Between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models Aaron Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Bin Hu

AAAI 2023 See Your Emotion from Gait Using Unlabeled Skeleton Data Haifeng Lu, Xiping Hu, Bin Hu

NeurIPS 2022 Global Convergence of Direct Policy Search for State-Feedback $\mathcal{H}_\infty$ Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential Xingang Guo, Bin Hu

ICML 2022 Provable Acceleration of Heavy Ball Beyond Quadratics for a Class of Polyak-Lojasiewicz Functions When the Non-Convexity Is Averaged-Out Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu

NeurIPS 2021 Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar

IJCAI 2021 Multi-Level Graph Encoding with Structural-Collaborative Relation Learning for Skeleton-Based Person Re-Identification Haocong Rao, Shihao Xu, Xiping Hu, Jun Cheng, Bin Hu

CVPR 2021 Weakly-Supervised Instance Segmentation via Class-Agnostic Learning with Salient Images Xinggang Wang, Jiapei Feng, Bin Hu, Qi Ding, Longjin Ran, Xiaoxin Chen, Wenyu Liu

NeurIPS 2020 On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems Kaiqing Zhang, Bin Hu, Tamer Basar

L4DC 2020 Policy Learning of MDPs with Mixed Continuous/Discrete Variables: A Case Study on Model-Free Control of Markovian Jump Systems Joao Paulo Jansch-Porto, Bin Hu, Geir Dullerud

L4DC 2020 Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence Kaiqing Zhang, Bin Hu, Tamer Basar

IJCAI 2020 Self-Supervised Gait Encoding with Locality-Aware Attention for Person Re-Identification Haocong Rao, Siqi Wang, Xiping Hu, Mingkui Tan, Huang Da, Jun Cheng, Bin Hu

NeurIPS 2019 Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory Bin Hu, Usman Syed

ICML 2018 Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs Bin Hu, Stephen Wright, Laurent Lessard

ICLR 2018 Learning Intrinsic Sparse Structures Within Long Short-Term Memory Wei Wen, Yuxiong He, Samyam Rajbhandari, Minjia Zhang, Wenhan Wang, Fang Liu, Bin Hu, Yiran Chen, Hai Li

ICCV 2017 A Joint Intrinsic-Extrinsic Prior Model for Retinex Bolun Cai, Xianming Xu, Kailing Guo, Kui Jia, Bin Hu, Dacheng Tao

COLT 2017 A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints Bin Hu, Peter Seiler, Anders Rantzer

ICML 2017 Dissipativity Theory for Nesterov’s Accelerated Method Bin Hu, Laurent Lessard