Papers by MohammadHossein Rezaei
Making Language Models Robust Against Negation (2025.naacl-long)
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| Challenge: | Negation is a semantic phenomenon that alters an expression to convey the opposite meaning. |
| Approach: | They propose a self-supervised method to make language models more robust against negation by pre-training models. |
| Outcome: | The proposed task outperforms the off-the-shelf versions on nine negation-related benchmarks. |
Paraphrasing in Affirmative Terms Improves Negation Understanding (2024.acl-short)
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| Challenge: | Negation is a common linguistic phenomenon in human languages . however, language models face challenges with negation in many tasks . |
| Approach: | They propose to incorporate affirmative interpretations into models to make them more robust against negation. |
| Outcome: | The proposed models are more robust against negation when negation is present in input . the proposed models can be used to analyze large corpus and natural language understanding tasks . |
Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding (2026.findings-acl)
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| Challenge: | Negation is a common and important semantic feature in natural language, yet Large Language Models struggle when negation is involved in natural learning tasks. |
| Approach: | They propose to augment existing corpora with negation by automatically augmenting existing ones with negations by combining multiple triples with if-then relations. |
| Outcome: | The proposed approach yields two new corpora containing over 2M triples with if-then relations. |
Interpreting Indirect Answers to Yes-No Questions in Multiple Languages (2023.findings-emnlp)
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Zijie Wang, Md Hossain, Shivam Mathur, Terry Melo, Kadir Ozler, Keun Park, Jacob Quintero, MohammadHossein Rezaei, Shreya Shakya, Md Uddin, Eduardo Blanco
| Challenge: | Existing models for Yes-no questions skip polar keywords and instead use long explanations that must be interpreted. |
| Approach: | They propose a distant supervision approach to collect training data and show that direct answers are useful to train models to interpret indirect answers. |
| Outcome: | The proposed model achieves a 68% to 76% F1-score on multilingual Question-Answering benchmarks. |
EgoNormia: Benchmarking Physical-Social Norm Understanding (2025.findings-acl)
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| Challenge: | Existing VLMs lack robust grounded norm understanding, a new study finds . current VLM models lack robust grounding, despite a high score for safety and privacy . |
| Approach: | They propose a pipeline to generate grounded MCQs from ego-centric videos of human interactions. |
| Outcome: | The proposed pipeline can generate grounded MCQs from egocentric video . it shows that current VLMs lack robust grounded norm understanding . |