Atabak Ashfaq

Artificial Intelligence · 2020–2025

A researcher in the Science corpus: 3 papers; trusts 27 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 102 citations into it; #19,157 of 35,345 by trust here, #15,236 by citations
• Natural Language Processing — 63 citations into it; #5,128 of 5,688 by trust here, #3,687 by citations
• Evaluation & Benchmarks — 56 citations into it; #1,836 of 3,147 by trust here, #2,040 by citations

Whom Atabak Ashfaq trusts overall

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

1. Chin-Yew Lin
2. Maxime Peyrard
3. Yvette Graham
4. Ani Nenkova
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Christopher D. Manning
8. Diederik P. Kingma
9. Ramesh Nallapati
10. Ilya Sutskever

Who trusts Atabak Ashfaq overall

1. Sebastian Gehrmann
2. Pierre Colombo
3. Daniel Deutsch

Papers from Atabak Ashfaq's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet classification with deep convolutional neural networks
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Gradient-based learning applied to document recognition
10. ImageNet: A large-scale hierarchical image database

Their papers

• Re-evaluating Evaluation in Text Summarization (2020) — 216 citations
• Metrics also Disagree in the Low Scoring Range: Revisiting Summarization Evaluation Metrics (2020) — 20 citations
• Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs (2025) — 509 citations