9 papers
Informal Learning Emerges in Everyday Human-LLM Interaction
Zixin Chen, Haotian Li, Ziang Xiao +2
As LLMs become increasingly capable of completing tasks for users, a central concern is that everyday AI use may become primarily cognitive offloading, eroding the opportunities th…
Multi-agent AI systems outperform human teams in creativity
Tiancheng Hu, Yixuan Jiang, Haotian Li +5
Although artificial intelligence (AI) now matches or exceeds human performance across numerous cognitive tasks, creativity remains a highly contested frontier. As AI systems based…
PersonaArena: Dynamic Simulation for Evaluating and Enhancing Persona-Level Role-Playing in Large Language Models
Wenlong Shi, Jianxun Lian, Mingqi Wu +5
Large language models (LLMs) increasingly serve as interactive social agents, yet their ability to maintain coherent and authentic persona-level role-playing remains limited, parti…
Does Theory of Mind Improvement Really Benefit Human-AI Interactions? Empirical Findings from Interactive Evaluations
Nanxu Gong, Zixin Chen, Haotian Li +5
Improving the Theory of Mind (ToM) capability of Large Language Models (LLMs) is crucial for effective social interactions between these AI models and humans. However, the existing…
From Passive Consumption to Active Interaction: Exploring Interactive LLM Scaffolding to Support Learning Engagement
Zixin Chen, Haotian Li, Zhe Liu +2
Large Language Models (LLMs) are increasingly used as learning companions, providing scaffolded explanations, hints, or step-by-step guidance. However, in current LLM-based learnin…
Interaction-Augmented Instruction: Modeling the Synergy of Prompts and Interactions in Human-GenAI Collaboration
Leixian Shen, Yifang Wang, Huamin Qu +2
Text prompt is the most common way for human-generative AI (GenAI) communication. Though convenient, it is challenging to convey fine-grained and referential intent. One promising…