ICLR 2026 - Submissions

SubmissionsReviews

Submissions

Summary Statistics

Quantity AI Content Count Avg Rating
0-10% 0 (0%) N/A
10-30% 0 (0%) N/A
30-50% 1 (100%) 3.50
50-70% 0 (0%) N/A
70-90% 0 (0%) N/A
90-100% 0 (0%) N/A
Total 1 (100%) 3.50
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
Non-Additive Time-Series Forecasting via Cross-Decomposition and Linear Attention Many multivariate forecasters model additive effects well but miss non-additive interactions among temporal bases, variables, and exogenous drivers, which harms long-horizon accuracy and attribution. ... 3.50 41% See Reviews View AI Dashboard
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