2 citations · 4 across the 5 of their papers we have counts for
7 papers
From Momentary Emotion Inference to Sustained Emotion Support: Evaluating a Companion Agent in a Longitudinal Study
Kexin Quan, Zijian Ding, Jiaye Yong +3
Sustained emotional support is a long-horizon interaction task closely tied to human well-being. Recent research demonstrates generative agents' capacity for momentary emotional su…
AGWM: Affordance-Grounded World Models for Environments with Compositional Prerequisites
Qinshi Zhang, Weipeng Deng, Zhihan Jiang +4
In model-based learning, the agent learns behaviors by simulating trajectories based on world model predictions. Standard world models typically learn a stationary transition funct…
Mixed-Initiative Context: Structuring and Managing Context for Human-AI Collaboration
Haichang Li, Qinshi Zhang, Piaohong Wang +1
In the human-AI collaboration area, the context formed naturally through multi-turn interactions is typically flattened into a chronological sequence and treated as a fixed whole i…
Frontend Diffusion: Empowering Self-Representation of Junior Researchers and Designers Through Multi-agent System
Zijian Ding, Qinshi Zhang, Mohan Chi +1
With the continuous development of generative AI's logical reasoning abilities, AI's growing code-generation potential poses challenges for both technical and creative professional…
Can AI Prompt Humans? Multimodal Agents Prompt Players' Game Actions and Show Consequences to Raise Sustainability Awareness
Qinshi Zhang, Ruoyu Wen, Latisha Besariani Hendra +2
Unsustainable behaviors are challenging to prevent due to their long-term, often unclear consequences. Games offer a promising solution by creating artificial environments where pl…
Frontend Diffusion: Exploring Intent-Based User Interfaces through Abstract-to-Detailed Task Transitions
Qinshi Zhang, Latisha Besariani Hendra, Mohan Chi +1
The emergence of Generative AI is catalyzing a paradigm shift in user interfaces from command-based to intent-based outcome specification. In this paper, we explore abstract-to-det…