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% 1 (100%) 1.50
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%) 1.50
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
What Is Missing: Interpretable Ratings for Large Language Model Outputs Current Large Language Model (LLM) preference learning methods such as Proximal Policy Optimization and Direct Preference Optimization rely on direct rankings or numerical ratings of model outputs as ... 1.50 0% See Reviews View AI Dashboard
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