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