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cs.LG2025
A Unified Frequency Domain Decomposition Framework for Interpretable and Robust Time Series Forecasting
Cheng He, Xijie Liang, Zengrong Zheng +6
Current approaches for time series forecasting, whether in the time or frequency domain, predominantly use deep learning models based on linear layers or transformers. They often e…
cs.LG2025
Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning
Gangwei Jiang, Caigao Jiang, Zhaoyi Li +5
Catastrophic forgetting (CF) poses a significant challenge in machine learning, where a model forgets previously learned information upon learning new tasks. Despite the advanced c…
cs.LG2025
GTM: A General Time-series Model for Enhanced Representation Learning of Time-Series Data
Cheng He, Xu Huang, Gangwei Jiang +7
Despite recent progress in time-series foundation models, challenges persist in improving representation learning and adapting to diverse downstream tasks. We introduce a General T…