Learning Decision-Stump Thresholds in Context: Dynamics of Softmax Attention
Estimating a decision threshold requires locating observations near an unknown boundary. We study how gradient-based pretraining learns this statistical rule in a two-parameter softmax-attention model with a fixed feature and inequality direction.
By Hong Ha Le, Jackie Lok, Atsushi Nitanda, Yan Shuo TanarXiv - stat.ML
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Originally published by arXiv - stat.ML on Oct 7, 2026.
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