Publications

Can Cui, Jiaru Zhang, Yupeng Zhou, Juntong Peng, Sung-Yeon Park, Zichong Yang, Prashanth Sankaranarayanan, Ruqi Zhang, Ziran Wang (2026). ViLaD: A Large Vision Language Diffusion Framework for End-to-End Autonomous Driving. In IROS.

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Jiaru Zhang, Manav Gagvani, Can Cui, Juntong Peng, Ruqi Zhang, Ziran Wang (2026). Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion. In IROS.

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Xiaoyu Wu, Jiaru Zhang, Yang Hua, Bohan Lyu, Hao Wang, Tao Song, Haibing Guan (2026). Exploring Diffusion Models' Corruption Stage in Few-Shot Fine-tuning and Mitigating with Bayesian Neural Networks. In SIGKDD.

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Jiaru Zhang, Juanwu Lu, Xiaoyu Wu, Ziran Wang, Ruqi Zhang (2026). Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding. In TMLR (Featured Certification).

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Pascal Jutras-Dubé, Jiaru Zhang, Ziran Wang, Ruqi Zhang (2026). One-Step Diffusion Samplers via Self-Distillation and Deterministic Flow. In AISTATS.

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Can Cui, Yunsheng Ma, Sung-Yeon Park, Zichong Yang, Yupeng Zhou, Peiran Liu, Juanwu Lu, Juntong Peng, Jiaru Zhang, Ruqi Zhang, Lingxi Li, Yaobin Chen, Jitesh H. Panchal, Amr Abdelraouf, Rohit Gupta, Kyungtae Han, Ziran Wang (2026). LLM4AD: Large Language Models for Autonomous Driving—Concept, Review, Benchmark, Experiments, and Future Trends. In Proceedings of the IEEE.

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Jiaru Zhang, Zesong Wang, Hao Wang, Tao Song, Huai-an Su, Rui Chen, Yang Hua, Xiangwei Zhou, Ruhui Ma, Miao Pan, Haibing Guan (2025). AMPERE: A Generic Energy Estimation Approach for On-Device Training. In ACM SIGMETRICS Performance Evaluation Review.

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Qingqian Yang, Peishen Yan, Xiaoyu Wu, Jiaru Zhang, Tao Song, Yang Hua, Hao Wang, Liangliang Wang, Haibing Guan (2025). Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-wise Gradient Alignment. In ICCV.

Xiaoyu Wu, Jiaru Zhang, Steven Wu (2025). Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models. In ICML.

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Jiaru Zhang, Rui Ding, Qiang Fu, Bojun Huang, Zizhen Deng, Yang Hua, Haibing Guan, Shi Han, Dongmei Zhang (2025). Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning. In AISTATS.

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Xiaoyu Wu, Yang Hua, Chumeng Liang, Jiaru Zhang, Hao Wang, Tao Song, Haibing Guan (2024). CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion. In CVPR.

Pingchuan Ma, Rui Ding, Qiang Fu, Jiaru Zhang, Shuai Wang, Shi Han, Dongmei Zhang (2024). SPOT: Harnessing Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior. In SIGKDD.

Jiaru Zhang, Yang Hua, Tao Song, Hao Wang, Zhengui Xue, Ruhui Ma, Haibing Guan (2023). Information Bound and its Applications in Bayesian Neural Networks. In ECAI.

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Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan (2023). Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples. In ICML (oral).

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Jiaru Zhang, Yang Hua, Tao Song, Hao Wang, Zhengui Xue, Ruhui Ma, Haibing Guan (2022). Improving Bayesian Neural Networks by Adversarial Sampling. In AAAI.

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Jiaru Zhang, Ruhui Ma, Tao Song, Yang Hua, Zhengui Xue, Chenyang Guan, Haibing Guan (2022). Hierarchical Satellite System Graph for Approximate Nearest Neighbor Search on Big Data. ACM/IMS Transactions on Data Science.

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Jiaru Zhang, Yang Hua, Zhengui Xue, Tao Song, Chengyu Zheng, Ruhui Ma, Haibing Guan (2021). Robust Bayesian Neural Networks by Spectral Expectation Bound Regularization. In CVPR.

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