Nasrin Mostafazadeh
Natural Language Processing · 2015–2020
A researcher in the Science corpus: 9 papers; trusts 270 researchers and is trusted by 41 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 160 citations into it; #1,590 of 5,688 by trust here, #924 by citations
- Artificial Intelligence — 139 citations into it; #7,125 of 35,345 by trust here, #3,304 by citations
- Computer Vision and Pattern Recognition — 101 citations into it; #8,374 of 21,575 by trust here, #2,519 by citations
- Multimodal Learning — 45 citations into it; #685 of 1,211 by trust here, #477 by citations
- Evaluation & Benchmarks — 40 citations into it; #1,388 of 3,147 by trust here, #748 by citations
- Information Systems — 11 citations into it
- Model Architectures — 10 citations into it
- Information Retrieval & Search — 6 citations into it
Whom Nasrin Mostafazadeh trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya Sutskever
- Nathanael Chambers
- George A. Miller
- Geoffrey E. Hinton
- Yoshua Bengio
- Karen Simonyan
- Alex Krizhevsky
- Chin-Yew Lin
- Diederik P. Kingma
- Tomas Mikolov
Who trusts Nasrin Mostafazadeh overall
- Qiang Ning
- Sarah Wiegreffe
- Hannah Rashkin
- Kurt Shuster
- Nanyun Peng
- Unnat Jain
- Rujun Han
- Varun Prashant Gangal
- Minlie Huang
- Sudha Rao
Papers from Nasrin Mostafazadeh's perspective
Ordered by how strongly the researchers Nasrin Mostafazadeh trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories (2016) — 827 citations
- Visual Storytelling (2016) — 543 citations
- Generating Natural Questions About an Image (2016) — 315 citations
- A Survey of Current Datasets for Vision and Language Research (2015) — 77 citations
- Image-Grounded Conversations: Multimodal Context for Natural Question and Response Generation (2017) — 193 citations
- LSDSem 2017 Shared Task: The Story Cloze Test (2017) — 195 citations
- CaTeRS: Causal and Temporal Relation Scheme for Semantic Annotation of Event Structures (2016) — 145 citations
- GLUCOSE: GeneraLized and COntextualized Story Explanations (2020) — 131 citations
- Tackling the Story Ending Biases in The Story Cloze Test (2018) — 87 citations