Ahmed Magooda


pdf bib
Exploring Multitask Learning for Low-Resource Abstractive Summarization
Ahmed Magooda | Diane Litman | Mohamed Elaraby
Findings of the Association for Computational Linguistics: EMNLP 2021

This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different tasks (extractive summarization, language modeling, concept detection, and paraphrase detection) both individually and in combination, with the goal of enhancing the target task of abstractive summarization via multitask learning. We show that for many task combinations, a model trained in a multitask setting outperforms a model trained only for abstractive summarization, with no additional summarization data introduced. Additionally, we do a comprehensive search and find that certain tasks (e.g. paraphrase detection) consistently benefit abstractive summarization, not only when combined with other tasks but also when using different architectures and training corpora.

pdf bib
Mitigating Data Scarceness through Data Synthesis, Augmentation and Curriculum for Abstractive Summarization
Ahmed Magooda | Diane Litman
Findings of the Association for Computational Linguistics: EMNLP 2021

This paper explores three simple data manipulation techniques (synthesis, augmentation, curriculum) for improving abstractive summarization models without the need for any additional data. We introduce a method of data synthesis with paraphrasing, a data augmentation technique with sample mixing, and curriculum learning with two new difficulty metrics based on specificity and abstractiveness. We conduct experiments to show that these three techniques can help improve abstractive summarization across two summarization models and two different small datasets. Furthermore, we show that these techniques can improve performance when applied in isolation and when combined.


pdf bib
RDI_Team at SemEval-2016 Task 3: RDI Unsupervised Framework for Text Ranking
Ahmed Magooda | Amr Gomaa | Ashraf Mahgoub | Hany Ahmed | Mohsen Rashwan | Hazem Raafat | Eslam Kamal | Ahmad Al Sallab
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)