activity
20242026
most citedRevisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

49 citations · 51 across the 2 of their papers we have counts for

collaborators

6 papers

cs.AI20262 cited

Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security

Jinhu Qi, Muzhi Li, Jiahong Liu +9

Agentic AI systems -- Large Language Models (LLMs) augmented with planning, tool use, memory, and long-horizon interactions -- can execute complex tasks autonomously, but their mul…

cs.LG202649 cited

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping

Zhe Li, Shiyi Qi, Yiduo Li +1

Introduction: Long-term time series forecasting (LTSF) has gained significant attention in recent years. While various specialized designs exist for capturing temporal dependency,…

cs.CL2025

Position: LLMs Can be Good Tutors in English Education

Jingheng Ye, Shen Wang, Deqing Zou +8

While recent efforts have begun integrating large language models (LLMs) into English education, they often rely on traditional approaches to learning tasks without fully embracing…

cs.LG2025

Online Optimization for Learning to Communicate over Time-Correlated Channels

Zheshun Wu, Junfan Li, Zenglin Xu +2

Machine learning techniques have garnered great interest in designing communication systems owing to their capacity in tackling with channel uncertainty. To provide theoretical gua…

eess.SP2024

FedCVD: The First Real-World Federated Learning Benchmark on Cardiovascular Disease Data

Yukun Zhang, Guanzhong Chen, Zenglin Xu +6

Cardiovascular diseases (CVDs) are currently the leading cause of death worldwide, highlighting the critical need for early diagnosis and treatment. Machine learning (ML) methods c…

cs.LG2024

On the Necessity of Collaboration for Online Model Selection with Decentralized Data

Junfan Li, Zheshun Wu, Zenglin Xu +1

We consider online model selection with decentralized data over clients, and study the necessity of collaboration among clients. Previous work proposed various federated algori…