ICLR 2026 - Submissions
Submissions
Summary Statistics
| Quantity AI Content | Count | Avg Rating |
|---|---|---|
| 0-10% | 0 (0%) | N/A |
| 10-30% | 1 (100%) | 3.50 |
| 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%) | 3.50 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| KPF: DOMINATING MULTI-AGENT ADVERSARIAL COMPETITION VIA KALMAN-INSPIRED POLICY FU- SION MECHANISM | Despite rapid advancements in Multi-Agent Reinforcement Learning (MARL), its application to complex, highly stochastic, and dynamic environments has been hindered by limitations in generalization capa... | 3.50 | 20% | See Reviews | View AI Dashboard |