Papers by Shane Arora
CaLMQA: Exploring culturally specific long-form question answering across 23 languages (2025.acl-long)
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| Challenge: | Despite rising global usage of large language models, their ability to generate *long-form* answers to *culturally specific* questions remains unexplored in many languages. |
| Approach: | They perform the first study of textual multilingual long-form QA by creating a dataset of culturally specific questions across 23 different languages. |
| Outcome: | The results show that the best models make critical surface-level errors for many languages and their understanding of diverse cultures. |