ICLR 2026 - Submissions

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Submissions

Quantity AI Content: 0-10%10-30%30-50%50-70%70-90%90-100%All
Avg Rating: 0-11-22-33-44-55-66-77-88-99-10All

Summary Statistics

Quantity AI Content Count Avg Rating
0-10% 0 (0%) N/A
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30-50% 0 (0%) N/A
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Total 1 (100%) 5.50
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
Shift-and-Sum Quantization for Visual Autoregressive Models Post-training quantization (PTQ) enables efficient deployment of deep networks using a small set of data. Its application to visual autoregressive models (VAR), however, remains relatively unexplored.... 5.50 N/A See Reviews
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