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% | 0 (0%) | N/A |
| 90-100% | 1 (100%) | 2.50 |
| Total | 1 (100%) | 2.50 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| DyCodeExplainer: Explainable Dynamic Graph Attention for Multi-Agent Reinforcement Learning in Collaborative Coding | We propose \textbf{DyCodeExplainer}, a novel multi-agent reinforcement learning (MARL) framework that integrates dynamic graph attention with explainability techniques to improve collaborative coding.... | 2.50 | 95% | See Reviews | View AI Dashboard |