Symbol Description

Symbol description research explores how symbols, both human-created and machine-learned, represent meaning and facilitate communication and reasoning in various domains, from natural language processing to robotics and computer-aided design. Current research focuses on developing models that can automatically learn and generate symbolic representations from data, often employing deep neural networks, transformers, and techniques like symbolic equation learning and point cloud segmentation. This work is significant for advancing artificial intelligence by bridging the gap between subsymbolic and symbolic approaches, leading to more interpretable, robust, and efficient systems with applications in diverse fields like software engineering, optimization, and educational technology.