Papers by Mohamed Abdelfattah
ArtELingo: A Million Emotion Annotations of WikiArt with Emphasis on Diversity over Language and Culture (2022.emnlp-main)
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Youssef Mohamed, Mohamed Abdelfattah, Shyma Alhuwaider, Feifan Li, Xiangliang Zhang, Kenneth Church, Mohamed Elhoseiny
| Challenge: | ArtELingo is a benchmark and dataset designed to encourage work on diversity across languages and cultures. |
| Approach: | They introduce a benchmark and dataset designed to encourage work on diversity across languages and cultures. |
| Outcome: | The new benchmark and dataset compared artELingo annotations across languages and cultures and found that diversity improves the performance of baseline models. |
ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models (2024.emnlp-main)
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Yash Akhauri, Ahmed AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander Rush, Safeen Huda, Mohamed Abdelfattah
| Challenge: | Prior work has focused on contextual sparsity, but it has not been successful. |
| Approach: | They propose a novel pruning predictor that can shadow the LLM behavior and enforce better sparsity patterns. |
| Outcome: | The proposed model can shadow the LLM behavior and enforce better sparsity patterns, resulting in 15% improvement in end-to-end accuracy compared to prior methods. |