ICLR 2026 - Submissions

SubmissionsReviews

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
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