ICLR 2026 - Submissions
Submissions
Summary Statistics
| Quantity AI Content | Count | Avg Rating |
|---|---|---|
| 0-10% | 0 (0%) | N/A |
| 10-30% | 0 (0%) | N/A |
| 30-50% | 0 (0%) | N/A |
| 50-70% | 1 (100%) | 4.00 |
| 70-90% | 0 (0%) | N/A |
| 90-100% | 0 (0%) | N/A |
| Total | 1 (100%) | 4.00 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| Logarithmic Regret in Preference Learning via Optimistic PAC-Bayesian Particle Ensembles | The remarkable sample efficiency of preference-based reinforcement learning, which underpins the alignment of large language models with human feedback (RLHF), presents a significant theoretical puzzl... | 4.00 | 65% | See Reviews | View AI Dashboard |