MLLMs given the same instructions as human participants achieve expert-level performance on perceiving stress in network visualizations and rely on similar visual proxies.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2025 2verdicts
UNVERDICTED 2representative citing papers
ParamInter is a guided visual interpolation tool for high-dimensional parameter space analysis that integrates t-SNE and XAI to support optimization, demonstrated on blast furnace modeling.
citing papers explorer
-
Exploring MLLMs Perception of Network Visualization Principles
MLLMs given the same instructions as human participants achieve expert-level performance on perceiving stress in network visualizations and rely on similar visual proxies.
-
Parameter Space Analysis through Guided Visual Interpolations
ParamInter is a guided visual interpolation tool for high-dimensional parameter space analysis that integrates t-SNE and XAI to support optimization, demonstrated on blast furnace modeling.