ICLR 2026 - Submissions

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Submissions

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Quantity AI Content Count Avg Rating
0-10% 1 (100%) 4.67
10-30% 0 (0%) N/A
30-50% 0 (0%) N/A
50-70% 0 (0%) N/A
70-90% 0 (0%) N/A
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Total 1 (100%) 4.67
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
BEYOND IMITATION: RECOVERING DENSE REWARDS FROM DEMONSTRATIONS Conventionally, supervised fine-tuning (SFT) is treated as a simple imitation learning process that only trains a policy to imitate expert behavior on demonstration datasets. In this work, we challeng... 4.67 4% See Reviews View AI Dashboard
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