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ORCIDJiaru Zhang
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2020 – today
- 2026
[j3]Jiaru Zhang, Juanwu Lu, Xiaoyu Wu, Ziran Wang, Ruqi Zhang:
Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding. Trans. Mach. Learn. Res. 2026 (2026)- [j2]Lingsheng Yang, Yu Lu, Jiaru Zhang, Jun Dong:
Design of a Lightweight Dual-Band Antenna for UAV Applications. Wirel. Pers. Commun. 146(2): 909-934 (2026) - [c10]Xiaoyu Wu
, Jiaru Zhang, Yang Hua, Bohan Lyu, Hao Wang, Tao Song, Haibing Guan:
Exploring Diffusion Models' Corruption Stage in Few-Shot Fine-tuning and Mitigating with Bayesian Neural Networks. KDD (1) 2026: 1590-1601 - [i17]Tianyi Zeng, Tianyi Wang, Jiaru Zhang, Zimo Zeng, Feiyang Zhang, Yiming Xu, Sikai Chen, Yajie Zou, Yangyang Wang, Junfeng Jiao, Christian G. Claudel, Xinbo Chen:
PILD: Physics-Informed Learning via Diffusion. CoRR abs/2601.21284 (2026) - [i16]Jiaru Zhang, Manav Gagvani, Can Cui, Juntong Peng, Ruqi Zhang, Ziran Wang:
Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion. CoRR abs/2602.20577 (2026) - [i15]Peishen Yan, Yang Hua, Hao Wang, Jiaru Zhang, Xiaoyu Wu, Tao Song, Haibing Guan:
FedMomentum: Preserving LoRA Training Momentum in Federated Fine-Tuning. CoRR abs/2603.08014 (2026) - [i14]Jiaru Zhang, Zeyun Deng, Juanwu Lu, Ziran Wang, Ruqi Zhang:
Analytical Correction for Subsampling Bias in Drifting Models. CoRR abs/2604.27239 (2026) - [i13]Bohan Lyu, Yucheng Yang, Siqiao Huang, Jiaru Zhang, Qixin Xu, Xinghan Li, Xinyang Han, Yicheng Zhang, Huaqing Zhang, Runhan Huang, Kaicheng Yang, Zitao Chen, Wentao Guo, Junlin Yang, Xinyue Ai, Wenhao Chai, Yadi Cao, Ziran Yang, Kun Wang, Dapeng Jiang, Huan-ang Gao, Shange Tang, Chengshuai Shi, Simon S. Du, Max Simchowitz, Jiantao Jiao, Dawn Song, Chi Jin:
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI. CoRR abs/2605.08678 (2026) - [i12]Zizhen Deng, Jiaru Zhang, Rui Ding, Bojun Huang, Jinzhuo Wang, Qiang Fu, Shi Han, Dongmei Zhang:
Test Time Training for Supervised Causal Learning. CoRR abs/2605.30015 (2026) - 2025
- [c9]Jiaru Zhang, Rui Ding, Qiang Fu, Bojun Huang, Zizhen Deng, Yang Hua, Haibing Guan, Shi Han, Dongmei Zhang:
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning. AISTATS 2025: 577-585 - [c8]Qingqian Yang, Peishen Yan, Xiaoyu Wu, Jiaru Zhang, Tao Song, Yang Hua, Hao Wang, Liangliang Wang, Haibing Guan:
Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-Wise Gradient Alignment. ICCV 2025: 29163-29172 - [c7]Xiaoyu Wu, Jiaru Zhang, Steven Wu:
Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models. ICML 2025 - [i11]Jiaru Zhang, Zesong Wang, Hao Wang, Tao Song, Huai-an Su, Rui Chen, Yang Hua, Xiangwei Zhou, Ruhui Ma, Miao Pan, Haibing Guan:
THOR: A Generic Energy Estimation Approach for On-Device Training. CoRR abs/2501.16397 (2025) - [i10]Jiaru Zhang, Rui Ding, Qiang Fu, Bojun Huang, Zizhen Deng, Yang Hua, Haibing Guan, Shi Han, Dongmei Zhang:
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning. CoRR abs/2502.10883 (2025) - [i9]Jiaru Zhang, Juanwu Lu, Ziran Wang, Ruqi Zhang:
Inference Acceleration of Autoregressive Normalizing Flows by Selective Jacobi Decoding. CoRR abs/2505.24791 (2025) - [i8]Can Cui, Yupeng Zhou, Juntong Peng, Sung-Yeon Park, Zichong Yang, Prashanth Sankaranarayanan, Jiaru Zhang, Ruqi Zhang, Ziran Wang:
ViLaD: A Large Vision Language Diffusion Framework for End-to-End Autonomous Driving. CoRR abs/2508.12603 (2025) - [i7]Mingyang Jiang, Yueyuan Li, Jiaru Zhang, Songan Zhang, Min Yang:
A Diffusion-Refined Planner with Reinforcement Learning Priors for Confined-Space Parking. CoRR abs/2510.14000 (2025) - [i6]Pascal Jutras-Dube, Jiaru Zhang, Ziran Wang, Ruqi Zhang:
One-Step Diffusion Samplers via Self-Distillation and Deterministic Flow. CoRR abs/2512.05251 (2025) - 2024
- [c6]Xiaoyu Wu, Yang Hua, Chumeng Liang, Jiaru Zhang, Hao Wang, Tao Song, Haibing Guan:
CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion. CVPR 2024: 10812-10821 - [c5]Pingchuan Ma, Rui Ding, Qiang Fu, Jiaru Zhang, Shuai Wang, Shi Han, Dongmei Zhang:
Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior. KDD 2024: 2141-2152 - [i5]Xiaoyu Wu, Yang Hua, Chumeng Liang, Jiaru Zhang, Hao Wang, Tao Song, Haibing Guan:
CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion. CoRR abs/2403.11162 (2024) - [i4]Xiaoyu Wu, Jiaru Zhang, Yang Hua, Bohan Lyu, Hao Wang, Tao Song, Haibing Guan:
Exploring Diffusion Models' Corruption Stage in Few-Shot Fine-tuning and Mitigating with Bayesian Neural Networks. CoRR abs/2405.19931 (2024) - [i3]Pingchuan Ma, Rui Ding, Qiang Fu, Jiaru Zhang, Shuai Wang, Shi Han, Dongmei Zhang:
Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version). CoRR abs/2406.10537 (2024) - [i2]Xiaoyu Wu, Jiaru Zhang, Steven Wu:
Revealing the Unseen: Guiding Personalized Diffusion Models to Expose Training Data. CoRR abs/2410.03039 (2024) - 2023
- [c4]Jiaru Zhang, Yang Hua, Tao Song, Hao Wang, Zhengui Xue, Ruhui Ma, Haibing Guan:
Information Bound and Its Applications in Bayesian Neural Networks. ECAI 2023: 3010-3017 - [c3]Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan:
Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples. ICML 2023: 20763-20786 - [i1]Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan:
Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples. CoRR abs/2302.04578 (2023) - 2022
- [c2]Jiaru Zhang, Yang Hua, Tao Song, Hao Wang, Zhengui Xue, Ruhui Ma, Haibing Guan:
Improving Bayesian Neural Networks by Adversarial Sampling. AAAI 2022: 10110-10117 - 2021
- [j1]Jiaru Zhang, Ruhui Ma, Tao Song, Yang Hua, Zhengui Xue, Chenyang Guan, Haibing Guan:
Hierarchical Satellite System Graph for Approximate Nearest Neighbor Search on Big Data. Trans. Data Sci. 2(4): 32:1-32:15 (2021) - [c1]Jiaru Zhang, Yang Hua, Zhengui Xue, Tao Song, Chengyu Zheng, Ruhui Ma, Haibing Guan:
Robust Bayesian Neural Networks by Spectral Expectation Bound Regularization. CVPR 2021: 3815-3824
Coauthor Index
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