Jiaru Zhang

According to our database, Jiaru Zhang authored at least 26 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Test Time Training for Supervised Causal Learning.

Zizhen Deng, Jiaru Zhang, Rui Ding, Bojun Huang, Jinzhuo Wang, Qiang Fu, Shi Han, Dongmei Zhang

CoRR, May, 2026

MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI.

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

CoRR, May, 2026

Analytical Correction for Subsampling Bias in Drifting Models.

Jiaru Zhang, Zeyun Deng, Juanwu Lu, Ziran Wang, Ruqi Zhang

CoRR, April, 2026

FedMomentum: Preserving LoRA Training Momentum in Federated Fine-Tuning.

Peishen Yan, Yang Hua, Hao Wang, Jiaru Zhang, Xiaoyu Wu, Tao Song, Haibing Guan

CoRR, March, 2026

Design of a Lightweight Dual-Band Antenna for UAV Applications.

Lingsheng Yang, Yu Lu, Jiaru Zhang, Jun Dong

Wirel. Pers. Commun., February, 2026

Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion.

Jiaru Zhang, Manav Gagvani, Can Cui, Juntong Peng, Ruqi Zhang, Ziran Wang

CoRR, February, 2026

PILD: Physics-Informed Learning via Diffusion.

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

CoRR, January, 2026

Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding.

Jiaru Zhang, Juanwu Lu, Xiaoyu Wu, Ziran Wang, Ruqi Zhang

Trans. Mach. Learn. Res., 2026

Exploring Diffusion Models' Corruption Stage in Few-Shot Fine-tuning and Mitigating with Bayesian Neural Networks.

Xiaoyu Wu, Jiaru Zhang, Yang Hua, Bohan Lyu, Hao Wang, Tao Song, Haibing Guan

Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

2025

One-Step Diffusion Samplers via Self-Distillation and Deterministic Flow.

Pascal Jutras-Dube, Jiaru Zhang, Ziran Wang, Ruqi Zhang

CoRR, December, 2025

A Diffusion-Refined Planner with Reinforcement Learning Priors for Confined-Space Parking.

Mingyang Jiang, Yueyuan Li, Jiaru Zhang, Songan Zhang, Min Yang

CoRR, October, 2025

ViLaD: A Large Vision Language Diffusion Framework for End-to-End Autonomous Driving.

Can Cui, Yupeng Zhou, Juntong Peng, Sung-Yeon Park, Zichong Yang, Prashanth Sankaranarayanan, Jiaru Zhang, Ruqi Zhang, Ziran Wang

CoRR, August, 2025

Inference Acceleration of Autoregressive Normalizing Flows by Selective Jacobi Decoding.

Jiaru Zhang, Juanwu Lu, Ziran Wang, Ruqi Zhang

CoRR, May, 2025

THOR: A Generic Energy Estimation Approach for On-Device Training.

Jiaru Zhang, Zesong Wang, Hao Wang, Tao Song, Huai-an Su, Rui Chen, Yang Hua, Xiangwei Zhou, Ruhui Ma, Miao Pan, Haibing Guan

CoRR, January, 2025

Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models.

Xiaoyu Wu, Jiaru Zhang, Steven Wu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-Wise Gradient Alignment.

Qingqian Yang, Peishen Yan, Xiaoyu Wu, Jiaru Zhang, Tao Song, Yang Hua, Hao Wang, Liangliang Wang, Haibing Guan

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning.

Jiaru Zhang, Rui Ding, Qiang Fu, Bojun Huang, Zizhen Deng, Yang Hua, Haibing Guan, Shi Han, Dongmei Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Revealing the Unseen: Guiding Personalized Diffusion Models to Expose Training Data.

Xiaoyu Wu, Jiaru Zhang, Steven Wu

CoRR, 2024

Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version).

Pingchuan Ma, Rui Ding, Qiang Fu, Jiaru Zhang, Shuai Wang, Shi Han, Dongmei Zhang

CoRR, 2024

Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior.

Pingchuan Ma, Rui Ding, Qiang Fu, Jiaru Zhang, Shuai Wang, Shi Han, Dongmei Zhang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion.

Xiaoyu Wu, Yang Hua, Chumeng Liang, Jiaru Zhang, Hao Wang, Tao Song, Haibing Guan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples.

Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan

Proceedings of the International Conference on Machine Learning, 2023

Information Bound and Its Applications in Bayesian Neural Networks.

Jiaru Zhang, Yang Hua, Tao Song, Hao Wang, Zhengui Xue, Ruhui Ma, Haibing Guan

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022

Improving Bayesian Neural Networks by Adversarial Sampling.

Jiaru Zhang, Yang Hua, Tao Song, Hao Wang, Zhengui Xue, Ruhui Ma, Haibing Guan

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Hierarchical Satellite System Graph for Approximate Nearest Neighbor Search on Big Data.

Jiaru Zhang, Ruhui Ma, Tao Song, Yang Hua, Zhengui Xue, Chenyang Guan, Haibing Guan

Trans. Data Sci., 2021

Robust Bayesian Neural Networks by Spectral Expectation Bound Regularization.

Jiaru Zhang, Yang Hua, Zhengui Xue, Tao Song, Chengyu Zheng, Ruhui Ma, Haibing Guan

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021