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CogME: A Cognition-Inspired Multi-Dimensional Evaluation Metric for Story Understanding
April 19, 2024, 4:45 a.m. | Minjung Shin, Seongho Choi, Yu-Jung Heo, Minsu Lee, Byoung-Tak Zhang, Jeh-Kwang Ryu
cs.CV updates on arXiv.org arxiv.org
Abstract: We introduce CogME, a cognition-inspired, multi-dimensional evaluation metric designed 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 …
abstract ai models arxiv assessment breakdown cognition cs.ai cs.cv evaluation framework human questions story strategies thinking type understanding
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