Conceptual Representation

Conceptual representation research investigates how concepts are encoded and processed, aiming to understand both human cognition and artificial intelligence. Current research focuses on aligning the conceptual representations of large language models (LLMs) and multimodal models like CLIP with human understanding, often using techniques like typicality effect analysis and semantic feature verification. This work is significant because it helps bridge the gap between human and machine intelligence, potentially leading to more explainable AI and improved applications in areas such as computer vision and natural language processing.