학술논문

CogME: A Cognition-Inspired Multi-Dimensional Evaluation Metric for Story Understanding
Document Type
article
Source
Proceedings of the Annual Meeting of the Cognitive Science Society. 46
Subject
Computer Science
Psychology
Human Factors
Language understanding
Computer-based experiment
Language
Abstract
We introduce CogME, a cognition-inspired, multi-dimensional evaluation metric for AI models focusing on story understanding. CogME is a framework grounded in human thinking strategies and story elements that involve story understanding. With a specific breakdown of the questions, this approach provides a nuanced assessment revealing not only AI models' particular strengths and weaknesses but also the characteristics of the benchmark dataset. Our case study with the DramaQA dataset demonstrates a refined analysis of the model and the benchmark dataset. It is imperative that metrics align closely with human cognitive processes by comprehending the tasks' nature. This approach provides insights beyond traditional overall scores and paves the way for more sophisticated AI development targeting higher cognitive functions.