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CAUS: A Dataset for Question Generation based on Human Cognition Leveraging Large Language Models
We introduce the CAUS (Curious About Uncertain Scene) dataset, designed to enable Large Language Models, specifically GPT-4, to emulate human cognitive processes for resolving uncertainties.
Toward a Human-Level Video Understanding Intelligence
In this paper, we propose the Video Turing Test to provide effective and practical assessments of video understanding intelligence as well as human-likeness evaluation of AI agents.
CogME: A Cognition-Inspired Multi-Dimensional Evaluation Metric for Story Understanding
We introduce CogME, a cognition-inspired, multi-dimensional evaluation metric designed for AI models focusing on story understanding.
Constructing Hierarchical Q&A Datasets for Video Story Understanding
Video understanding is emerging as a new paradigm for studying human-like AI.
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