Papers by Hasan Mahmud
Math Word Problem Solving by Generating Linguistic Variants of Problem Statements (2023.acl-srw)
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Syed Rifat Raiyan, Md Nafis Faiyaz, Shah Md. Jawad Kabir, Mohsinul Kabir, Hasan Mahmud, Md Kamrul Hasan
| Challenge: | Existing models for solving Math Word Problems depend on shallow heuristics and spurious correlations to derive the solution expressions. |
| Approach: | They propose a framework for MWP solvers based on generation of linguistic variants of problem text. |
| Outcome: | The proposed framework improves the mathematical reasoning and robustness of the proposed model. |
BanglaBook: A Large-scale Bangla Dataset for Sentiment Analysis from Book Reviews (2023.findings-acl)
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| Challenge: | Existing literature on Bangla Sentiment Analysis (SA) has limited data and cross-domain adaptability. |
| Approach: | They present a large-scale dataset of Bangla book reviews with 158,065 samples . they employ a range of machine learning models to establish baselines including SVM, LSTM, and Bangla-BERT. |
| Outcome: | The proposed model improves performance over models that rely on manual features. |
“When Words Fail, Emojis Prevail”: A Novel Architecture for Generating Sarcastic Sentences With Emoji Using Valence Reversal and Semantic Incongruity (2023.acl-srw)
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Faria Binte Kader, Nafisa Hossain Nujat, Tasmia Binte Sogir, Mohsinul Kabir, Hasan Mahmud, Md Kamrul Hasan
| Challenge: | Existing sarcasm generation tasks focus on textual sarcasm, but people often use emojis to express their emotions. |
| Approach: | They propose a novel architecture for sarcasm generation with emojis from a non-sarcastic input sentence in English. |
| Outcome: | The proposed architecture generates sarcastic outputs with emojis from a non-sarcastic input sentence in english. |