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
10-30% 0 (0%) N/A
30-50% 1 (100%) 3.33
50-70% 0 (0%) N/A
70-90% 0 (0%) N/A
90-100% 0 (0%) N/A
Total 1 (100%) 3.33
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
Rethinking RL Evaluation: Can Benchmarks Truly Reveal Failures of RL Methods? Current benchmarks are inadequate for evaluating progress in reinforcement learning (RL) for large language models (LLMs).Despite recent benchmark gains reported for RL, we find that training on these... 3.33 38% See Reviews View AI Dashboard
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