With enough compute, large models benefit from training on unfiltered data that includes low-quality and distractor examples instead of requiring high-quality filtered data.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Optimizer choice induces distinct connected regions in the loss landscape of two-layer ReLU networks, with AdamW and Muon sometimes separated by provable barriers.
citing papers explorer
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A Bitter Lesson for Data Filtering
With enough compute, large models benefit from training on unfiltered data that includes low-quality and distractor examples instead of requiring high-quality filtered data.
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Optimizer-Induced Mode Connectivity: From AdamW to Muon
Optimizer choice induces distinct connected regions in the loss landscape of two-layer ReLU networks, with AdamW and Muon sometimes separated by provable barriers.