@inproceedings{ki-etal-2026-graphicweaver,
    title = "{G}raphic{W}eaver: Benchmarking Agentic Planning for Graphic Design Generation",
    author = "Ki, Dayeon  and
      Zhou, Tianyi  and
      Carpuat, Marine  and
      Wu, Gang  and
      Mathur, Puneet  and
      Swaminathan, Viswanathan",
    editor = "Yan, Qianqi  and
      Montariol, Syrielle  and
      Fan, Yue  and
      Gu, Jing  and
      Pan, Jiayi  and
      Li, Manling  and
      Kordjamshidi, Parisa  and
      Suhr, Alane  and
      Wang, Xin Eric",
    booktitle = "Proceedings of the 4th Workshop on Advances in Language and Vision Research ({ALVR})",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.alvr-main.5/",
    pages = "57--84",
    ISBN = "979-8-89176-398-2",
    abstract = "Vision-language model (VLM)-powered agents are increasingly enabling new forms of automation across various human tasks. While prior work has primarily focused on well-defined problems with explicit goals, the capabilities of agents in creative graphic design, where goals are inherently open-ended and subjective, remain largely underexplored.To bridge this gap, we introduce GraphicWeaver, a planning benchmark for graphic design comprising 1,079 diverse user queries and associated images spanning four design categories.Comprehensive experiments with six models reveal that current VLM-based agents struggle to handle such complex planning tasks, which require taking into account both explicit design constraints specified in queries and implicit commonsense design principles. We attribute these failures to challenges in (1) retrieving appropriate parameters for tool usage, (2) understanding spatial relationships across design components, and (3) coordinating dependencies across agents. We envision GraphicWeaver as a challenging yet valuable testbed for advancing VLM agent planning in creative design contexts."
}