Papers by SeyedAbolghasem Mirroshandel
Deep Active Learning for Morphophonological Processing (2023.acl-short)
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Seyed Morteza Mirbostani, Yasaman Boreshban, Salam Khalifa, SeyedAbolghasem Mirroshandel, Owen Rambow
| Challenge: | Existing deep learning models for morphological processing require a large amount of annotated data. |
| Approach: | They propose a deep active learning method that uses only informative samples to reduce the need for annotated data. |
| Outcome: | The proposed method achieves the same results as the state-of-the-art model on Egyptian Arabic with only about 30% of annotated data. |
Opinion Mining Using Pre-Trained Large Language Models: Identifying the Type, Polarity, Intensity, Expression, and Source of Private States (2024.lrec-main)
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Saeed Ahmadnia, Arash Yousefi Jordehi, Mahsa Hosseini Khasheh Heyran, SeyedAbolghasem Mirroshandel, Owen Rambow
| Challenge: | Existing research on opinion mining has focused on a small subset of the MPQA 2.0 dataset . a recent study focused on the subjective expressions of people who express opinions, sentiments, and attitudes toward targets. |
| Approach: | They propose to use MPQA 2.0 to analyze the entire dataset . they propose to provide a clean version of the MPQA Opinion Corpus in a more interpretable format . |
| Outcome: | The proposed methods establish high baselines for future work. |