Understanding in Artificial Intelligence
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Abstract (arXiv)
Current Artificial Intelligence (AI) methods, most based on deep learning, have facilitated progress in several fields, including computer vision and natural language understanding. The progress of these AI methods is measured using benchmarks designed to solve challenging tasks, such as visual question answering. A question remains of how much understanding is leveraged by these methods and how appropriate are the current benchmarks to measure understanding capabilities. To answer these questions, we have analysed existing benchmarks and their understanding capabilities, defined by a set of understanding capabilities, and current research streams. We show how progress has been made in benchmark development to measure understanding capabilities of AI methods and we review as well how current methods develop understanding capabilities.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 170 of its 279 references that are in the map. First posted on arXiv 17 Jan 2021.
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38 more
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