Human Understanding
Human understanding, a multifaceted field encompassing cognitive processes and AI model capabilities, seeks to unravel how humans and machines comprehend information. Current research focuses on improving AI's ability to understand nuanced language, visual information, and complex relationships within data, employing techniques like multimodal large language models, hypergraph attention networks, and retrieval-augmented generation. These advancements have implications for various applications, including improved medical diagnosis, enhanced human-computer interaction, and more effective scientific knowledge extraction, but challenges remain in achieving truly robust and generalizable understanding in AI.
Papers
Predicting the Understandability of Computational Notebooks through Code Metrics Analysis
Mojtaba Mostafavi Ghahfarokhi, Alireza Asadi, Arash Asgari, Bardia Mohammadi, Masih Beigi Rizi, Abbas Heydarnoori
Understanding Understanding: A Pragmatic Framework Motivated by Large Language Models
Kevin Leyton-Brown, Yoav Shoham