Qinshi (Carol) Zhang

@article{zhang2024frontend,
    title={Frontend Diffusion: Empowering Self-Representation of Researchers and Designers with Multi-agent System},
    author={Ding, Zijian, Zhang, Qinshi, Chi, Mohan, WANG, Ziyi},
    journal={arXiv e-prints},
    pages={arXiv--2408},
    year={2024}
}

@inproceedings{10.1145/3706598.3713661,
   author = {Zhang, Qinshi and Wen, Ruoyu and Hendra, Latisha Besariani and Ding, Zijian and LC, Ray},
   title = {Can AI Prompt Humans? Multimodal Agents Prompt Players? Game Actions and Show Consequences to Raise Sustainability Awareness},
   year = {2025},
   isbn = {9798400713941},
   publisher = {Association for Computing Machinery},
   address = {New York, NY, USA},
   url = {https://doi.org/10.1145/3706598.3713661},
   doi = {10.1145/3706598.3713661},
   abstract = {Unsustainable behaviors are challenging to prevent due to their long-term, often unclear consequences. Serious games offer a promising solution by creating artificial environments where players can immediately experience the outcomes of their actions. To explore this potential, we developed EcoEcho, a GenAI-powered game leveraging multimodal agents to raise sustainability awareness. These agents engage players in natural conversations, prompting them to take in-game actions that lead to visible environmental impacts. We evaluated EcoEcho using a mixed-methods approach with 23 participants. Results show a significant increase in intended sustainable behaviors post-game, although attitudes towards sustainability had only marginal effects, suggesting that in-game actions likely can motivate intended real world behaviors despite similar opinions on sustainability. This finding highlights multimodal agents and action-consequence mechanics to effectively raising sustainability awareness and the potential of motivating real-world behavioral change.},
   booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
   articleno = {1044},
   numpages = {29},
   keywords = {Multimodal Agents, Sustainability Awareness, Generative AI, In-Game Action},
   location = {},
   series = {CHI '25}
}

@inproceedings{zhou2024eternagram,
    title={Eternagram: Probing Player Attitudes Towards Climate Change Using a ChatGPT-driven Text-based Adventure},
    author={Zhou, Suifang and Hendra, Latisha Besariani and Zhang, Qinshi and Holopainen, Jussi and LC, RAY},
    booktitle={Proceedings of the CHI Conference on Human Factors in Computing Systems},
    pages={1--23},
    year={2024}
}

@article{zhang2026agwm,
    title={AGWM: Affordance-Grounded World Models for Environments with Compositional Prerequisites},
    author={Zhang, Qinshi and Deng, Weipeng and Jiang, Zhihan and Qu, Jiaming and Li, Qianren and Xu, Weitao and LC, Ray},
    journal={arXiv preprint arXiv:2605.06841},
    year={2026}
}

@article{li2026mixedinitiative,
    title={Mixed-Initiative Context: Structuring and Managing Context for Human-AI Collaboration},
    author={Li, Haichang and Zhang, Qinshi and Wang, Piaohong and Lu, Zhicong},
    journal={arXiv preprint arXiv:2604.07121},
    year={2026}
}