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%) | 3.00 |
| 70-90% | 0 (0%) | N/A |
| 90-100% | 0 (0%) | N/A |
| Total | 1 (100%) | 3.00 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| FedMAP: Meta-Driven Adaptive Differential Privacy for Federated Learning | Federated learning (FL) enables multiple clients to train a shared model without sharing raw data, but gradients can still leak sensitive information through inversion and membership inference attacks... | 3.00 | 62% | See Reviews | View AI Dashboard |