Human Like
Research on "human-like" qualities in artificial intelligence focuses on developing models that exhibit behaviors and cognitive abilities resembling those of humans, aiming to improve AI's interaction with and understanding of humans. Current research emphasizes evaluating and enhancing aspects like reasoning, language understanding, and emotional intelligence in large language models (LLMs) and other AI architectures, often employing techniques like cognitive prompting, psychometric analysis, and imitation learning. This work is significant for advancing AI safety and trustworthiness, improving human-computer interaction, and providing novel tools for psychological and cognitive science research.
Papers
Mixed Reality Teleoperation Assistance for Direct Control of Humanoids
Luigi Penco, Kazuhiko Momose, Stephen McCrory, Dexton Anderson, Nicholas Kitchel, Duncan Calvert, Robert J. Griffin
ReSpAct: Harmonizing Reasoning, Speaking, and Acting Towards Building Large Language Model-Based Conversational AI Agents
Vardhan Dongre, Xiaocheng Yang, Emre Can Acikgoz, Suvodip Dey, Gokhan Tur, Dilek Hakkani-Tür