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% | 1 (100%) | 4.50 |
| 50-70% | 0 (0%) | N/A |
| 70-90% | 0 (0%) | N/A |
| 90-100% | 0 (0%) | N/A |
| Total | 1 (100%) | 4.50 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| Certifying Robustness of Agent Tool-Selection Under Adversarial Attacks | Large language models (LLMs) are increasingly deployed in agentic systems where they map user intents to relevant external tools to fulfill a task. A critical step in this process is tool selection, w... | 4.50 | 41% | See Reviews | View AI Dashboard |