@inproceedings{jamshidi-etal-2026-framenet,
    title = "{F}rame{N}et-Cultures: A Benchmark for Evaluating {LLM}s via Cross-Cultural Frame Semantics",
    author = "Jamshidi, Neda  and
      S{\{}{\textbackslash}o{\}}gaard, Anders  and
      Bianchini, Monica",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.findings-acl.491/",
    pages = "10090--10131",
    ISBN = "979-8-89176-395-1",
    abstract = "Large language models (LLMs) exhibit cultural biases, yet existing benchmarks rely on closed-form, domain-specific questionnaires. We introduce FRAMENET-CULTURES, a benchmark for evaluating cultural alignment in LLMs based on Fillmore-style frame semantics. Using the EveryCulture encyclopedia, we construct a lexicon of 18 cultural frames (e.g., greeting,child-rearing) across 20 countries, treating it as a structured reference for comparison rather than a definitive representation of contemporary societies. For each frame, we prompt five major LLMs{---}ChatGPT-5, Gemini-2.5-Flash, Mistral-Large, Qwen-3-Max, DeepSeek-V3.2{---}three times to generate open-ended instantiations, which are manually annotated and binarized. We measure alignment with country- and continent-level profiles using normalized Hamming distance, and validate cultural recognizability through human evaluation of generated dialogues. Under culture-neutral prompting, outputs align most closely with European profiles, followed by Asian and American ones, indicating a consistent cross-model pattern. With culture-specific prompting, models shift toward the target regions, aligning most strongly with Africa for Ethiopia and with Asia for India. FRAMENET-CULTURES is the first open-ended benchmark for cultural alignment relying on frame semantics. Data, prompts, and annotations are publicly available at https://github.com/neda-jamshidi/FrameNet-Cultures."
}