Papers by Erfan Moosavi Monazzah
PerCul: A Story-Driven Cultural Evaluation of LLMs in Persian (2025.naacl-long)
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Erfan Moosavi Monazzah, Vahid Rahimzadeh, Yadollah Yaghoobzadeh, Azadeh Shakery, Mohammad Taher Pilehvar
| Challenge: | Large language models predominantly reflect Western cultures due to the dominance of English-centric training data. |
| Approach: | They propose a dataset to assess the sensitivity of LLMs to Persian culture. |
| Outcome: | The proposed model shows a 11.3% gap between best closed-source model and layperson baseline while the gap increases to 21.3% by using the best open-weight model. |
Synthia: Scalable Grounded Persona Generation from Social Media Data (2026.acl-long)
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| Challenge: | Persona-driven large language models (LLMs) are increasingly used in computational social science, yet their validity critically depends on the fidelity of the underlying personas. |
| Approach: | They propose a persona-generation framework that grounds LLM-generated personas in real social-media posts while delegating narrative construction to language models. |
| Outcome: | The proposed framework outperforms state-of-the-art methods for most demographics across different dimensions while maintaining interaction graph structure among personas grounded in real social network users. |