Sequential Data Classification in the Space of Liquid State Machines. - Yang Li 066; Junyuan Hong; Huanhuan Chen (ECML/PKDD (1), 2016)

Disturbance Grassmann Kernels for Subspace-Based Learning. - Junyuan Hong; Huanhuan Chen; Feng Lin (KDD, 2018)

Variant Grassmann Manifolds: A Representation Augmentation Method for Action Recognition. - Junyuan Hong; Yang Li 066; Huanhuan Chen (ACM Trans. Knowl. Discov. Data, 2019)

Short Sequence Classification Through Discriminable Linear Dynamical System. - Yang Li 066; Junyuan Hong; Huanhuan Chen (IEEE Trans. Neural Networks Learn. Syst., 2019)

Learning Model-Based Privacy Protection under Budget Constraints. - Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (AAAI, 2021)

Data-Free Knowledge Distillation for Heterogeneous Federated Learning. - Zhuangdi Zhu; Junyuan Hong; Jiayu Zhou (ICML, 2021)

Federated Adversarial Debiasing for Fair and Transferable Representations. - Junyuan Hong; Zhuangdi Zhu; Shuyang Yu; Zhangyang Wang; Hiroko H. Dodge; Jiayu Zhou (KDD, 2021)

On Dynamic Noise Influence in Differentially Private Learning. - Junyuan Hong; Zhangyang Wang; Jiayu Zhou (CoRR, 2021)

Federated Robustness Propagation: Sharing Adversarial Robustness in Federated Learning. - Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (CoRR, 2021)

Dynamic Privacy Budget Allocation Improves Data Efficiency of Differentially Private Gradient Descent. - Junyuan Hong; Zhangyang Wang; Jiayu Zhou (FAccT, 2022)

Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization. - Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (ICLR, 2022)

Resilient and Communication Efficient Learning for Heterogeneous Federated Systems. - Zhuangdi Zhu; Junyuan Hong; Steve Drew 001; Jiayu Zhou (ICML, 2022)

Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling. - Junyuan Hong; Lingjuan Lyu; Jiayu Zhou; Michael Spranger (NeurIPS, 2022)

Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork. - Haotao Wang; Junyuan Hong; Aston Zhang; Jiayu Zhou; Zhangyang Wang (NeurIPS, 2022)

Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning. - Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (AAAI, 2023)

MECTA: Memory-Economic Continual Test-Time Model Adaptation. - Junyuan Hong; Lingjuan Lyu; Jiayu Zhou; Michael Spranger (ICLR, 2023)

Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection. - Shuyang Yu; Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (ICLR, 2023)

Revisiting Data-Free Knowledge Distillation with Poisoned Teachers. - Junyuan Hong; Yi Zeng 005; Shuyang Yu; Lingjuan Lyu; Ruoxi Jia 001; Jiayu Zhou (ICML, 2023)

International Workshop on Federated Learning for Distributed Data Mining. - Junyuan Hong; Zhuangdi Zhu; Lingjuan Lyu; Yang Zhou 001; Vishnu Naresh Boddeti; Jiayu Zhou (KDD, 2023)

Understanding Deep Gradient Leakage via Inversion Influence Functions. - Haobo Zhang 002; Junyuan Hong; Yuyang Deng; Mehrdad Mahdavi; Jiayu Zhou (NeurIPS, 2023)

On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space. - Yuyang Deng; Nidham Gazagnadou; Junyuan Hong; Mehrdad Mahdavi; Lingjuan Lyu (CoRR, 2023)

FedNoisy: Federated Noisy Label Learning Benchmark. - Siqi Liang 001; Jintao Huang; Dun Zeng; Junyuan Hong; Jiayu Zhou; Zenglin Xu (CoRR, 2023)

Who Leaked the Model? Tracking IP Infringers in Accountable Federated Learning. - Shuyang Yu; Junyuan Hong; Yi Zeng 005; Fei Wang; Ruoxi Jia 001; Jiayu Zhou (CoRR, 2023)

How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts. - Haotao Wang; Junyuan Hong; Jiayu Zhou; Zhangyang Wang (Trans. Mach. Learn. Res., 2023)

On the Generalization Ability of Unsupervised Pretraining. - Yuyang Deng; Junyuan Hong; Jiayu Zhou; Mehrdad Mahdavi (AISTATS, 2024)

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer. - Junyuan Hong; Jiachen T. Wang; Chenhui Zhang; Zhangheng Li; Bo Li 026; Zhangyang Wang (ICLR, 2024)

Safe and Robust Watermark Injection with a Single OoD Image. - Shuyang Yu; Junyuan Hong; Haobo Zhang 002; Haotao Wang; Zhangyang Wang; Jiayu Zhou (ICLR, 2024)

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression. - Junyuan Hong; Jinhao Duan; Chenhui Zhang; Zhangheng Li; Chulin Xie; Kelsey Lieberman; James Diffenderfer; Brian R. Bartoldson; Ajay Kumar Jaiswal; Kaidi Xu; Bhavya Kailkhura; Dan Hendrycks; et al. (ICML, 2024)

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. - Yihua Zhang; Pingzhi Li; Junyuan Hong; Jiaxiang Li; Yimeng Zhang; Wenqing Zheng; Pin-Yu Chen; Jason D. Lee; Wotao Yin; Mingyi Hong 001; Zhangyang Wang; Sijia Liu 001; et al. (ICML, 2024)

FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics. - Junyuan Hong; Carl Yang 001; Zhuangdi Zhu; Zheng Xu 002; Nathalie Baracaldo; Neil Shah; Salman Avestimehr; Jiayu Zhou (KDD, 2024)

Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk. - Zhangheng Li; Junyuan Hong; Bo Li 026; Zhangyang Wang (SaTML, 2024)

GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning. - Zhen Xiang; Linzhi Zheng; Yanjie Li; Junyuan Hong; Qinbin Li; Han Xie; Jiawei Zhang 002; Zidi Xiong; Chulin Xie; Carl Yang 001; Dawn Song; Bo Li 026 (CoRR, 2024)

DeepOSets: Non-Autoregressive In-Context Learning of Supervised Learning Operators. - Shao-Ting Chiu; Junyuan Hong; Ulisses Braga-Neto (CoRR, 2024)

LLM-PBE: Assessing Data Privacy in Large Language Models. - Qinbin Li; Junyuan Hong; Chulin Xie; Jeffrey Tan; Rachel Xin; Junyi Hou; Xavier Yin; Zhun Wang; Dan Hendrycks; Zhangyang Wang; Bo Li 026; Bingsheng He; et al. (Proc. VLDB Endow., 2024)

Extracting and Understanding the Superficial Knowledge in Alignment. - Runjin Chen; Gabriel J. Perin; Xuxi Chen; Xilun Chen; Yan Han; Nina S. T. Hirata; Junyuan Hong; Bhavya Kailkhura (NAACL (Long Papers), 2025)

GuideLLM: Exploring LLM-Guided Conversation with Applications in Autobiography Interviewing. - Jinhao Duan; Xinyu Zhao; Zhuoxuan Zhang; Eunhye Grace Ko; Lily Boddy; Chenan Wang; Tianhao Li; Alexander Rasgon; Junyuan Hong; Min Kyung Lee; Chenxi Yuan; Qi Long; et al. (NAACL (Long Papers), 2025)

MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models. - Shrey Pandit; Jiawei Xu 006; Junyuan Hong; Zhangyang Wang; Tianlong Chen 001; Kaidi Xu; Ying Ding 001 (CoRR, 2025)

More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment. - Yifan Wang; Runjin Chen; Bolian Li; David Cho; Yihe Deng; Ruqi Zhang; Tianlong Chen 001; Zhangyang Wang; Ananth Grama; Junyuan Hong (CoRR, 2025)

SEAL: Steerable Reasoning Calibration of Large Language Models for Free. - Runjin Chen; Zhenyu Zhang 015; Junyuan Hong; Souvik Kundu 009; Zhangyang Wang (CoRR, 2025)

Scaling Textual Gradients via Sampling-Based Momentum. - Zixin Ding; Junyuan Hong; Jiachen T. Wang; Zinan Lin 001; Zhangyang Wang; Yuxin Chen (CoRR, 2025)

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning. - Gabriel J. Perin; Runjin Chen; Xuxi Chen; Nina S. T. Hirata; Zhangyang Wang; Junyuan Hong (CoRR, 2025)