Abstract
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](https://github.com/YuxiXie/ECHo).- Anthology ID:
- 2023.findings-emnlp.268
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4064–4085
- Language:
- URL:
- https://aclanthology.org/2023.findings-emnlp.268
- DOI:
- 10.18653/v1/2023.findings-emnlp.268
- Cite (ACL):
- Yuxi Xie, Guanzhen Li, and Min-Yen Kan. 2023. ECHo: A Visio-Linguistic Dataset for Event Causality Inference via Human-Centric Reasoning. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 4064–4085, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- ECHo: A Visio-Linguistic Dataset for Event Causality Inference via Human-Centric Reasoning (Xie et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.findings-emnlp.268.pdf