| 2025 | CIKM | In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks. | Shangqing Xu, Harshavardhan Kamarthi, Haoxin Liu, B. Aditya Prakash |
| 2025 | IECON | Residual-Enhanced Proximal Policy Optimization for Optimal Energy Management in Hybrid Energy Storage Systems. | Bin Chen, Haoyang Yan, Rui Zhang, Haoxin Liu, Miaobeng Wang, Wei Liu, Yucheng Zhang, Longyun Zhu, Kai Gao |
| 2025 | KDD | Performative Time-Series Forecasting. | Zhiyuan Zhao, Haoxin Liu, Alexander Rodrguez, B. Aditya Prakash |
| 2025 | NAACL | A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualization. | Haoxin Liu, Chenghao Liu, B. Aditya Prakash |
| 2024 | ACL | LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. | Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash |
| 2024 | ICML | Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. | Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash |
| 2023 | WWW | HAPENS: Hardness-Personalized Negative Sampling for Implicit Collaborative Filtering. | Haoxin Liu, Pu Zhao, Si Qin, Yong Shi, Mirror Xu, Qingwei Lin, Dongmei Zhang |
| 2022 | CIKM | Exploiting Global Behavior Contextual Correlation in Sequential Recommendation Augmentation. | Qian Yu, Xiangdong Wu, Chen Yang, Zihao Zhao, Haoxin Liu, Chaosheng Fan, Changping Peng, Zhangang Lin, Jinghe Hu, Jingping Shao |
| 2022 | CVPR | Towards Unsupervised Domain Generalization. | Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu |
| 2022 | SIGIR | LightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design. | Haoxin Liu |
| 2021 | KDD | Signed Graph Neural Network with Latent Groups. | Haoxin Liu, Ziwei Zhang, Peng Cui, Yafeng Zhang, Qiang Cui, Jiashuo Liu, Wenwu Zhu |