Xu Liu - RankMe

38 papers A* 7A 3Journal 22Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective. KDD (1) Yuchen Fang, Yuxuan Liang, Bo Hui, Zezhi Shao, Liwei Deng, Xu Liu, Xinke Jiang, Kai Zheng
2025	J	`jnl`	Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models. CoRR Xu Liu, Taha Aksu, Juncheng Liu, Qingsong Wen, Yuxuan Liang, Caiming Xiong, Silvio Savarese, Doyen Sahoo, Junnan Li, Chenghao Liu
2025	J	`jnl`	FlowNet: Modeling Dynamic Spatio-Temporal Systems via Flow Propagation. CoRR Yutong Feng, Xu Liu, Yutong Xia, Yuxuan Liang
2025	J	`jnl`	Moirai 2.0: When Less Is More for Time Series Forecasting. CoRR Chenghao Liu, Taha Aksu, Juncheng Liu, Xu Liu, Hanshu Yan, Quang Pham, Silvio Savarese, Doyen Sahoo, Caiming Xiong, Junnan Li
2025	A*	`conf`	Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts. ICML Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Yuxuan Liang, Roger Zimmermann, Chenghao Liu, Junnan Li, Silvio Savarese, Caiming Xiong, Doyen Sahoo
2025	—	`conf`	ST-LoRA: Low-Rank Adaptation for Spatio-Temporal Forecasting. ECML/PKDD (7) Weilin Ruan, Wei Chen, Xilin Dang, Jianxiang Zhou, Weichuang Li, Xu Liu, Yuxuan Liang
2024	J	`jnl`	A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading. CoRR Yuan Li, Bingqiao Luo, Qian Wang, Nuo Chen, Xu Liu, Bingsheng He
2024	A*	`conf`	CryptoTrade: A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading. EMNLP Yuan Li, Bingqiao Luo, Qian Wang, Nuo Chen, Xu Liu, Bingsheng He
2024	J	`jnl`	Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective. CoRR Yuchen Fang, Yuxuan Liang, Bo Hui, Zezhi Shao, Liwei Deng, Xu Liu, Xinke Jiang, Kai Zheng
2024	J	`jnl`	GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation. CoRR Taha Aksu, Gerald Woo, Juncheng Liu, Xu Liu, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo
2024	A*	`conf`	Improving Neural Logic Machines via Failure Reflection. ICML Zhiming Li, Yushi Cao, Yan Zheng, Xu Liu, Bozhi Wu, Tianlin Li, Xiufeng Xu, Junzhe Jiang, Yon Shin Teo, Shang-Wei Lin, Yang Liu
2024	—	`conf`	LLMs for Relational Reasoning: How Far are We? LLM4CODE@ICSE Zhiming Li, Yushi Cao, Xiufeng Xu, Junzhe Jiang, Xu Liu, Yon Shin Teo, Shang-Wei Lin, Yang Liu
2024	J	`jnl`	LLMs for Relational Reasoning: How Far are We? CoRR Zhiming Li, Yushi Cao, Xiufeng Xu, Junzhe Jiang, Xu Liu, Yon Shin Teo, Shang-Wei Lin, Yang Liu
2024	J	`jnl`	Low-rank Adaptation for Spatio-Temporal Forecasting. CoRR Weilin Ruan, Wei Chen, Xilin Dang, Jianxiang Zhou, Weichuang Li, Xu Liu, Yuxuan Liang
2024	J	`jnl`	Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts. CoRR Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Yuxuan Liang, Roger Zimmermann, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo
2024	A	`conf`	Prompt-Based Spatio-Temporal Graph Transfer Learning. CIKM Junfeng Hu, Xu Liu, Zhencheng Fan, Yifang Yin, Shili Xiang, Savitha Ramasamy, Roger Zimmermann
2024	J	`jnl`	Prompt-Enhanced Spatio-Temporal Graph Transfer Learning. CoRR Junfeng Hu, Xu Liu, Zhencheng Fan, Yifang Yin, Shili Xiang, Savitha Ramasamy, Roger Zimmermann
2024	—	`conf`	Reinventing Node-centric Traffic Forecasting for Improved Accuracy and Efficiency. ECML/PKDD (3) Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann
2024	A*	`conf`	Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting. NeurIPS Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang
2024	J	`jnl`	Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting. CoRR Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang
2024	—	`conf`	Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning. SIGSPATIAL/GIS Junfeng Hu, Xu Liu, Zhencheng Fan, Yuxuan Liang, Roger Zimmermann
2024	A*	`conf`	UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting. WWW Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang, Bryan Hooi, Roger Zimmermann
2024	A	`conf`	User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation. WSDM Hengchang Hu, Wei Guo, Xu Liu, Yong Liu, Ruiming Tang, Rui Zhang, Min-Yen Kan
2023	J	`jnl`	A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection. IEEE Trans. Knowl. Data Eng. Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Yuan Li, Xu Liu, Bingsheng He
2023	A*	`conf`	Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment. NeurIPS Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann
2023	J	`jnl`	Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment. CoRR Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann
2023	J	`jnl`	Do We Really Need Graph Neural Networks for Traffic Forecasting? CoRR Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann
2023	A*	`conf`	LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting. NeurIPS Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann
2023	J	`jnl`	LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting. CoRR Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann
2023	J	`jnl`	Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning. CoRR Junfeng Hu, Xu Liu, Zhencheng Fan, Yuxuan Liang, Roger Zimmermann
2023	J	`jnl`	UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting. CoRR Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang, Bryan Hooi, Roger Zimmermann
2022	J	`jnl`	The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems. ACM Trans. Intell. Syst. Technol. Sixu Hu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, Bingsheng He
2022	A	`conf`	TrajFormer: Efficient Trajectory Classification with Transformers. CIKM Yuxuan Liang, Kun Ouyang, Yiwei Wang, Xu Liu, Hongyang Chen, Junbo Zhang, Yu Zheng, Roger Zimmermann
2022	—	`conf`	When do contrastive learning signals help spatio-temporal graph forecasting? SIGSPATIAL/GIS Xu Liu, Yuxuan Liang, Chao Huang, Yu Zheng, Bryan Hooi, Roger Zimmermann
2021	J	`jnl`	Spatio-Temporal Graph Contrastive Learning. CoRR Xu Liu, Yuxuan Liang, Yu Zheng, Bryan Hooi, Roger Zimmermann
2020	J	`jnl`	OD Morphing: Balancing Simplicity with Faithfulness for OD Bundling. IEEE Trans. Vis. Comput. Graph. Yan Lyu, Xu Liu, Hanyi Chen, Arpan Mangal, Kai Liu, Chao Chen, Brian Y. Lim
2020	J	`jnl`	The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems. CoRR Sixu Hu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, Bingsheng He
2019	J	`jnl`	A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection. CoRR Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Xu Liu, Bingsheng He