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% | 0 (0%) | N/A |
| 70-90% | 1 (100%) | 2.00 |
| 90-100% | 0 (0%) | N/A |
| Total | 1 (100%) | 2.00 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| Structuring Semantic Embeddings for Principle Evaluation: A Kernel-Guided Contrastive Learning Approach | Evaluating principle adherence in high-dimensional text embeddings is challenging because principle-specific signals are often entangled with general semantic content. Our kernel-guided contrastive le... | 2.00 | 78% | See Reviews | View AI Dashboard |