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cs.LG2026
Architecture-driven Shift: towards a lightweight selector for capturing the trends of logit shift
Zhong Ye, Yu Hu, Ruilin Tang
Continual Learning (CL) is a practical paradigm to utilize power of deep pre-trained neural networks, but which pre-trained model has a better ability to balance ``Plasticity-Stabi…
cs.LG2026
CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models
Xiaorui Wang, Fanda Fan, Chenxi Wang +9
Recent progress in time-series forecasting has led to rapidly increasing architectural complexity, yet many reported State-of-the-Art gains are statistically fragile or misattribut…