Papers by Seyed Mohammad Hadi Hosseini

2 papers
MEENA (PersianMMMU): Multimodal-Multilingual Educational Exams for N-level Assessment (2026.findings-eacl)

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Challenge: Recent advances in large vision-language models have primarily focused on English, with limited attention given to other languages.
Approach: They propose a dataset to evaluate Persian VLMs across scientific, reasoning, and human-level understanding tasks.
Outcome: The proposed model performs well across scientific reasoning, reasoning, and human-level understanding tasks in Persian and English.
CER: Confidence Enhanced Reasoning in LLMs (2025.acl-long)

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Challenge: Existing approaches to enhance the reliability of Large Language Models (LLMs) in complex reasoning tasks are limited by their limitations.
Approach: They propose an uncertainty-aware framework to enhance the reliability of Large Language Models . they quantify the confidence of intermediate answers and evaluate the reliability based on these confidences a way that reflects the reliability.
Outcome: The proposed approach improves accuracy of large language models in math and open-domain tasks by 7.4% and 5.8% over baseline approaches.

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