ICLR 2026 - Submissions
Submissions
Summary Statistics
| Quantity AI Content | Count | Avg Rating |
|---|---|---|
| 0-10% | 0 (0%) | N/A |
| 10-30% | 1 (100%) | 2.00 |
| 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%) | 2.00 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| Are complicated loss functions necessary for teaching LLMs to reason? | Recent advances in large language models (LLMs) highlight the importance of post-training techniques for improving reasoning and mathematical ability. Group Relative Policy Optimization (GRPO) has sho... | 2.00 | 21% | See Reviews | View AI Dashboard |