activity
20242026
collaborators

7 papers

cs.LG2026

Exact Federated Continual Unlearning for Ridge Heads on Frozen Foundation Models

Yijun Quan, Wentai Wu, Giovanni Montana

Foundation models are commonly deployed as frozen feature extractors with a small trainable head to adapt to private, user-generated data in federated settings. The ``right to be f…

cs.LG2026

\textsc{Lethe}: Principled Dual-Stream Update for Persistent Knowledge Erasure in Federated Unlearning

Wentai Wu, Hanwei Tan, Yijun Quan +4

Federated unlearning (FU) aims to erase knowledge from a global model. Existing studies commonly assume that federated collaboration terminates after unlearning, overlooking a depl…

cs.LG2026

Seeing the Needle in the Haystack: Towards Weakly-Supervised Log Instance Anomaly Localization via Counterfactual Perturbation

Yutszyuk Wong, Wentai Wu, Yuen-Ying Yeung +1

Log anomaly detection is a critical task for system operations and security assurance. However, in networked systems at scale, log data are generated at massive scale while instanc…

cs.IR2026

HaS: Accelerating RAG through Homology-Aware Speculative Retrieval

Peng Peng, Weiwei Lin, Wentai Wu +2

Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) at inference by retrieving external documents as context. However, retrieval bec…

cs.DC2025

Task-Agnostic Federation over Decentralized Data: Research Landscape and Visions

Wentai Wu, Ligang He, Saiqin Long +4

Increasing legislation and regulations on private and proprietary information results in scattered data sources also known as the "data islands". Although Federated Learning-based…

cs.LG2024

CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns

Shengsheng Lin, Weiwei Lin, Xinyi Hu +3

The stable periodic patterns present in time series data serve as the foundation for conducting long-horizon forecasts. In this paper, we pioneer the exploration of explicitly mode…