A benchmark of 3,744 TikZ scientific diagrams and 18.3k human-validated questions shows models answer diagram questions well (up to 86% accuracy) but parse diagrams into code poorly (object-level F1 31-57%), with agentic tools helping coding but hurting question answering.
Gpt-5.2.https://developers.openai.com/api/docs/models/gpt-5.2, 2025
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Diagram-MMU: A Multi-Modal Benchmark for Scientific Diagrams
A benchmark of 3,744 TikZ scientific diagrams and 18.3k human-validated questions shows models answer diagram questions well (up to 86% accuracy) but parse diagrams into code poorly (object-level F1 31-57%), with agentic tools helping coding but hurting question answering.