| 2026 | AAAI | Scalable Multi-Objective and Meta Reinforcement Learning via Gradient Estimation. | Zhenshuo Zhang, Minxuan Duan, Youran Ye, Hongyang R. Zhang |
| 2026 | KDD | Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning. | Dongyue Li, Zhenshuo Zhang, Minxuan Duan, Edgar Dobriban, Hongyang R. Zhang |
| 2026 | KDD | Learning Multimodal Embeddings for Traffic Accident Prediction and Causal Estimation. | Ziniu Zhang, Minxuan Duan, Haris N. Koutsopoulos, Hongyang R. Zhang |
| 2025 | ACL | Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets. | Dongyue Li, Ziniu Zhang, Lu Wang, Hongyang R. Zhang |
| 2025 | EMNLP | Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation. | Ziniu Zhang, Zhenshuo Zhang, Dongyue Li, Lu Wang, Jennifer G. Dy, Hongyang R. Zhang |
| 2024 | KDD | Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity. | Dongyue Li, Aneesh Sharma, Hongyang R. Zhang |
| 2023 | AAAI | Information Transfer in Multitask Learning, Data Augmentation, and Beyond. | Hongyang R. Zhang |
| 2023 | AISTATS | Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion. | Haotian Ju, Dongyue Li, Aneesh Sharma, Hongyang R. Zhang |
| 2023 | KDD | Boosting Multitask Learning on Graphs through Higher-Order Task Affinities. | Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang |
| 2023 | SDM | Optimal Intervention on Weighted Networks via Edge Centrality. | Dongyue Li, Tina Eliassi-Rad, Hongyang R. Zhang |
| 2022 | ICML | Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees. | Haotian Ju, Dongyue Li, Hongyang R. Zhang |
| 2022 | ICML | Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations. | Michael Zhang, Nimit Sharad Sohoni, Hongyang R. Zhang, Chelsea Finn, Christopher R |
| 2021 | MICCAI | Observational Supervision for Medical Image Classification Using Gaze Data. | Khaled Saab, Sarah M. Hooper, Nimit Sharad Sohoni, Jupinder Parmar, Brian Pogatchnik, Sen Wu, Jared A. Dunnmon, Hongyang R. Zhang, Daniel L. Rubin, Christopher R |
| 2020 | COLT | Learning Over-Parametrized Two-Layer Neural Networks beyond NTK. | Yuanzhi Li, Tengyu Ma, Hongyang R. Zhang |
| 2020 | ICLR | Understanding and Improving Information Transfer in Multi-Task Learning. | Sen Wu, Hongyang R. Zhang, Christopher R |
| 2020 | ICML | On the Generalization Effects of Linear Transformations in Data Augmentation. | Sen Wu, Hongyang R. Zhang, Gregory Valiant, Christopher R |