Real Human
Research on "Real Human" focuses on understanding and replicating human capabilities, particularly in perception, cognition, and social interaction, using artificial intelligence models. Current efforts concentrate on developing and evaluating large language models (LLMs) and large vision-language models (LVLMs), often incorporating architectures like transformers and diffusion models, to benchmark AI performance against human benchmarks in tasks ranging from visual perception and emotion recognition to complex decision-making and social interaction. These studies aim to improve AI systems' alignment with human behavior and understanding, ultimately impacting fields like human-computer interaction, robotics, and social sciences.
Papers
Aiding Humans in Financial Fraud Decision Making: Toward an XAI-Visualization Framework
Angelos Chatzimparmpas, Evanthia Dimara
MagicMan: Generative Novel View Synthesis of Humans with 3D-Aware Diffusion and Iterative Refinement
Xu He, Xiaoyu Li, Di Kang, Jiangnan Ye, Chaopeng Zhang, Liyang Chen, Xiangjun Gao, Han Zhang, Zhiyong Wu, Haolin Zhuang
Towards Neural Network based Cognitive Models of Dynamic Decision-Making by Humans
Changyu Chen, Shashank Reddy Chirra, Maria José Ferreira, Cleotilde Gonzalez, Arunesh Sinha, Pradeep Varakantham
Collaboration Between Robots, Interfaces and Humans: Practice-Based and Audience Perspectives
Anna Savery, Richard Savery