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% 0 (0%) N/A
50-70% 1 (100%) 3.50
70-90% 0 (0%) N/A
90-100% 0 (0%) N/A
Total 1 (100%) 3.50
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
MIMIC-VQA: COMPILING AGENTIC REASONERS INTO EFFICIENT DOCUMENT VQA MODELS Document Visual Question Answering systems face a fundamental architectural dichotomy: modular agentic frameworks decompose problems into interpretable sub-tasks but incur prohibitive inference latenc... 3.50 69% See Reviews View AI Dashboard
PreviousPage 1 of 1 (1 total rows)Next