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Routing Absorption in Sparse Attention: Why Random Gates Are Hard to Beat

Aquino-Michaels, Keston
arXiv (OAI Expanded) · Papers
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computation-and-languagemachine-learning
Learned gates can approximate sparse attention patterns on frozen transformers, yet provide limited benefit over random gates when trained jointly with the model. We investigate this difference in a controlled 31M-parameter transformer and attribute it to routing absorption: model representations co
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