ICLR 2026 - Submissions
Submissions
Summary Statistics
| Quantity AI Content | Count | Avg Rating |
|---|---|---|
| 0-10% | 1 (100%) | 3.00 |
| 10-30% | 0 (0%) | N/A |
| 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%) | 3.00 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| LEMUR: Leveraging Vision-Language Models for Fine-Grained Multimodal Retrieval | Fine-grained multimodal retrieval is crucial for many real-world applications. For example, E-commerce product search demands retrieving the product with the most relevant image and description based ... | 3.00 | 0% | See Reviews | View AI Dashboard |