InfoCausalQA : Can Models Perform Non-explicit Causal Reasoning Based on Infographic?
Published in preprint, 2025
InfoCausalQA—a benchmark of 494 infographic–text pairs with 1,482 human-revised MCQs generated via GPT-4o—tests quantitative trend reasoning and five semantic causal types (cause, effect, intervention, counterfactual, temporal) and shows that current VLMs, far below human performance, struggle with genuinely grounded causal inference from infographics.