3 citations · 4 across the 2 of their papers we have counts for
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cs.LG2025★ 3 cited
Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels
Yaxuan Wang, Hao Cheng, Jing Xiong +6
Detecting anomalies in temporal data has gained significant attention across various real-world applications, aiming to identify unusual events and mitigate potential hazards. In p…
cs.LG2024★ 1 cited
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
Hao Cheng, Qingsong Wen, Yang Liu +1
Time series forecasting is an important and forefront task in many real-world applications. However, most of time series forecasting techniques assume that the training data is cle…
cs.LG2023
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
Zhaowei Zhu, Jialu Wang, Hao Cheng +1
Language models have shown promise in various tasks but can be affected by undesired data during training, fine-tuning, or alignment. For example, if some unsafe conversations are…