Jun Wu - RankMe

40 papers A* 14A 4B 1Journal 18Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	HalluGuard: Demystifying Data-Driven and Reasoning-Driven Hallucinations in LLMs. CoRR Xinyue Zeng, Junhong Lin, Yujun Yan, Feng Guo, Liang Shi, Jun Wu, Dawei Zhou
2025	J	`jnl`	Data Value in the Age of Scaling: Understanding LLM Scaling Dynamics Under Real-Synthetic Data Mixtures. CoRR Haohui Wang, Jingyuan Qi, Jianpeng Chen, Jun Wu, Lifu Huang, Lecheng Zheng, Kevin Choi, Balaji Veeramani, Edward Bowen, Alison Hu, Tyler Cody, Dawei Zhou
2025	A	`conf`	Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem. AISTATS Katherine Tieu, Dongqi Fu, Jun Wu, Jingrui He
2025	J	`jnl`	Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem. CoRR Katherine Tieu, Dongqi Fu, Jun Wu, Jingrui He
2025	J	`jnl`	LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection. CoRR Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou
2025	A*	`conf`	LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection. ICML Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou
2025	J	`jnl`	Plan and Budget: Effective and Efficient Test-Time Scaling on Large Language Model Reasoning. CoRR Junhong Lin, Xinyue Zeng, Jie Zhu, Song Wang, Julian Shun, Jun Wu, Dawei Zhou
2025	A*	`conf`	Towards Trustworthy Machine Learning Under Distribution Shifts. AAAI Jun Wu
2025	J	`jnl`	Trustworthy Transfer Learning: A Survey. J. Artif. Intell. Res. Jun Wu, Jingrui He
2024	A	`conf`	BOBA: Byzantine-Robust Federated Learning with Label Skewness. AISTATS Wenxuan Bao, Jun Wu, Jingrui He
2024	A*	`conf`	Distributional Network of Networks for Modeling Data Heterogeneity. KDD Jun Wu, Jingrui He, Hanghang Tong
2024	—	`conf`	GPT Attack for Adversarial Privacy Policies. BigCom Isaac Joy, Jun Wu, Jingrui He
2024	J	`jnl`	Trustworthy Transfer Learning: A Survey. CoRR Jun Wu, Jingrui He
2023	J	`jnl`	A Unified Framework for Adversarial Attacks on Multi-Source Domain Adaptation. IEEE Trans. Knowl. Data Eng. Jun Wu, Jingrui He
2023	A*	`conf`	Graph-Structured Gaussian Processes for Transferable Graph Learning. NeurIPS Jun Wu, Lisa Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He
2023	A*	`conf`	Non-IID Transfer Learning on Graphs. AAAI Jun Wu, Jingrui He, Elizabeth A. Ainsworth
2023	A*	`conf`	Optimizing the Collaboration Structure in Cross-Silo Federated Learning. ICML Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He
2023	J	`jnl`	Optimizing the Collaboration Structure in Cross-Silo Federated Learning. CoRR Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He
2023	A*	`conf`	Personalized Federated Learning with Parameter Propagation. KDD Jun Wu, Wenxuan Bao, Elizabeth A. Ainsworth, Jingrui He
2023	A*	`conf`	Trustworthy Transfer Learning: Transferability and Trustworthiness. KDD Jun Wu, Jingrui He
2022	A*	`conf`	A Unified Meta-Learning Framework for Dynamic Transfer Learning. IJCAI Jun Wu, Jingrui He
2022	J	`jnl`	A Unified Meta-Learning Framework for Dynamic Transfer Learning. CoRR Jun Wu, Jingrui He
2022	B	`conf`	Adaptive Knowledge Transfer on Evolving Domains. IEEE Big Data Jun Wu, Hanghang Tong, Elizabeth A. Ainsworth, Jingrui He
2022	J	`jnl`	Adaptive Transfer Learning for Plant Phenotyping. CoRR Jun Wu, Elizabeth A. Ainsworth, Sheng Wang, Kaiyu Guan, Jingrui He
2022	A	`conf`	Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning. CIKM Yao Zhou, Jun Wu, Haixun Wang, Jingrui He
2022	A*	`conf`	Distribution-Informed Neural Networks for Domain Adaptation Regression. NeurIPS Jun Wu, Jingrui He, Sheng Wang, Kaiyu Guan, Elizabeth A. Ainsworth
2022	A*	`conf`	Domain Adaptation with Dynamic Open-Set Targets. KDD Jun Wu, Jingrui He
2022	J	`jnl`	Dynamic transfer learning with progressive meta-task scheduler. Frontiers Big Data Jun Wu, Jingrui He
2022	J	`jnl`	Non-IID Transfer Learning on Graphs. CoRR Jun Wu, Jingrui He, Elizabeth A. Ainsworth
2021	A*	`conf`	Indirect Invisible Poisoning Attacks on Domain Adaptation. KDD Jun Wu, Jingrui He
2021	A*	`conf`	PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network. KDD Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He
2020	—	`conf`	CANON: Complex Analytics of Network of Networks for Modeling Adversarial Activities. IEEE BigData Shane Roach, Connie Ni, Alexei Kopylov, Tsai-Ching Lu, Jiejun Xu, Si Zhang, Boxin Du, Dawei Zhou, Jun Wu, Lihui Liu, Yuchen Yan, Jingrui He, Hanghang Tong
2020	J	`jnl`	Continuous Transfer Learning with Label-informed Distribution Alignment. CoRR Jun Wu, Jingrui He
2020	J	`jnl`	GAN-based Recommendation with Positive-Unlabeled Sampling. CoRR Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He
2020	J	`jnl`	Robust Decentralized Learning for Neural Networks. CoRR Yao Zhou, Jun Wu, Jingrui He
2019	A*	`conf`	DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification. KDD Jun Wu, Jingrui He, Jiejun Xu
2019	J	`jnl`	DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification. CoRR Jun Wu, Jingrui He, Jiejun Xu
2019	A	`conf`	Scalable Manifold-Regularized Attributed Network Embedding via Maximum Mean Discrepancy. CIKM Jun Wu, Jingrui He
2018	—	`conf`	ImVerde: Vertex-Diminished Random Walk for Learning Imbalanced Network Representation. IEEE BigData Jun Wu, Jingrui He, Yongming Liu
2018	J	`jnl`	ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data. CoRR Jun Wu, Jingrui He, Yongming Liu