ICLR 2026 - Submissions

SubmissionsReviews

Submissions

Summary Statistics

Quantity AI Content Count Avg Rating
0-10% 1 (100%) 2.00
10-30% 0 (0%) N/A
30-50% 0 (0%) N/A
50-70% 0 (0%) N/A
70-90% 0 (0%) N/A
90-100% 0 (0%) N/A
Total 1 (100%) 2.00
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
Beyond Weight-Only: Mixed-Precision Quantization for BERT Weights, Activations and Embeddings Pre-trained language models deliver strong performance across various Natural Language Processing (NLP) tasks but remain costly to deploy due to memory and compute demands. To address this, model comp... 2.00 0% See Reviews View AI Dashboard
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