Conceptual Diversity

Conceptual diversity focuses on measuring and enhancing the variety of ideas or solutions within a system, whether it's a text, a neural network, or a set of optimization results. Current research explores quantifying this diversity using novel metrics, particularly within natural language processing and deep learning, and employs algorithms like quality diversity optimization to generate collections of diverse, high-performing solutions. This research is significant for improving the interpretability and performance of AI models, as well as for fostering creativity and innovation in various fields by promoting the exploration of a wider range of possibilities.

Papers