ISO-Bench: Benchmarking Multimodal Causal Reasoning in Visual-Language Models through Procedural Plans

• URL: http://arxiv.org/abs/2507.23135v1
• Date: Wed, 30 Jul 2025 22:30:48 GMT
• Title: ISO-Bench: Benchmarking Multimodal Causal Reasoning in Visual-Language Models through Procedural Plans
• Authors: Ananya Sadana, Yash Kumar Lal, Jiawei Zhou,
• Abstract summary: We introduce ISO-Bench, a benchmark for evaluating whether models can infer causal dependencies between visual observations and procedural text.<n> Evaluation results on ten frontier vision-language models show underwhelming performance.
• Score: 10.026145953509246
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Understanding causal relationships across modalities is a core challenge for multimodal models operating in real-world environments. We introduce ISO-Bench, a benchmark for evaluating whether models can infer causal dependencies between visual observations and procedural text. Each example presents an image of a task step and a text snippet from a plan, with the goal of deciding whether the visual step occurs before or after the referenced text step. Evaluation results on ten frontier vision-language models show underwhelming performance: the best zero-shot F1 is only 0.57, and chain-of-thought reasoning yields only modest gains (up to 0.62 F1), largely behind humans (0.98 F1). Our analysis further highlights concrete directions for improving causal understanding in multimodal models.

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