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%) | 3.33 |
| 50-70% | 0 (0%) | N/A |
| 70-90% | 0 (0%) | N/A |
| 90-100% | 0 (0%) | N/A |
| Total | 1 (100%) | 3.33 |
| Title | Abstract | Avg Rating | Quantity AI Content | Reviews | Pangram Dashboard |
|---|---|---|---|---|---|
| AgentXploit: End-to-End Red-Teaming for AI Agents Powdered by Multi-Agent Systems | AI agents, powered by Large Language Model (LLM), are vulnerable to indirect prompt injection attacks, where malicious data from external tools and data sources can manipulate agent behavior. Existing... | 3.33 | 34% | See Reviews | View AI Dashboard |