Bashar Alhafni

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 4 papers; trusts 55 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 70 citations into it; #30,602 of 35,345 by trust here, #34,213 by citations
• Natural Language Processing — 53 citations into it
• Safety, Robustness & Interpretability — 22 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Large Language Models — 7 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Model Architectures — 5 citations into it

Whom Bashar Alhafni trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Jieyu Zhao
3. Yoshua Bengio
4. Kyunghyun Cho
5. Dzmitry Bahdanau
6. Nizar Habash
7. Matt Post
8. Geoffrey E. Hinton
9. Jimmy Ba
10. Ilya Sutskever

Who trusts Bashar Alhafni overall

1. Emily Sheng
2. Rebecca Qian
3. Rujun Han
4. Kai-Wei Chang
5. Candace Ross
6. Nanyun Peng

Papers from Bashar Alhafni's perspective

Ordered by how strongly the researchers Bashar Alhafni trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Contextualized Word Embeddings Enhanced Event Temporal Relation Extraction for Story Understanding (2019) — 22 citations
• The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models (2021) — 379 citations
• Gender-Aware Reinflection using Linguistically Enhanced Neural Models (2020)
• Evaluating Prompt Relevance of Arabic Essays: Insights from Synthetic and Real-World Data