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We introduce ECHo (Event Causality Inference via Human-Centric Reasoning), adiagnostic dataset of event causality inference grounded in visio-linguisticsocial scenarios. ECHo employs real-world human-centric deductive informationbuilding on a television crime drama. ECHo requires the Theory-of-Mind (ToM)ability to understand and reason about social interactions based on multimodalinformation. Using ECHo, we propose a unified Chain-of-Thought (CoT) frameworkto assess the reasoning capability of current AI systems. Our ToM-enhanced CoTpipeline accommodates various large foundation models in both zero-shot andfew-shot visio-linguistic reasoning. We use this framework to scrutinize recentlarge foundation models such as InstructGPT and MiniGPT-4 on three diagnostichuman-centric tasks. Further analysis demonstrates ECHo as a challengingdataset to expose imperfections and inconsistencies in reasoning. Our data andcode are publicly available at https://github.com/YuxiXie/ECHo.

ECHo: A Visio-Linguistic Dataset for Event Causality Inference via Human-Centric Reasoning