ICLR 2026 - Submissions

SubmissionsReviews

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% 1 (100%) 5.33
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%) 5.33
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
Inverse IFEval: Can LLMs Unlearn Stubborn Training Conventions to Follow Real Instructions? Large Language Models (LLMs) achieve strong performance on diverse tasks but often exhibit cognitive inertia, struggling to follow instructions that conflict with the standardized patterns learned dur... 5.33 8% See Reviews View AI Dashboard
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