2 citations · 2 across the 13 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2025
Test time training enhances in-context learning of nonlinear functions
Kento Kuwataka, Taiji Suzuki
Test-time training (TTT) enhances model performance by explicitly updating designated parameters prior to each prediction to adapt to the test data. While TTT has demonstrated cons…
stat.ML2025
On the Role of Label Noise in the Feature Learning Process
Andi Han, Wei Huang, Zhanpeng Zhou +5
Deep learning with noisy labels presents significant challenges. In this work, we theoretically characterize the role of label noise from a feature learning perspective. Specifical…