Oshin Agarwal

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 6 papers; trusts 114 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 118 citations into it
• Natural Language Processing — 104 citations into it; #4,489 of 5,688 by trust here, #4,250 by citations
• Computer Vision and Pattern Recognition — 28 citations into it
• Evaluation & Benchmarks — 22 citations into it
• Safety, Robustness & Interpretability — 19 citations into it
• Large Language Models — 16 citations into it
• Information Systems — 13 citations into it
• Representation & Self-Supervised Learning — 13 citations into it

Whom Oshin Agarwal trusts overall

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

1. Kenton C. T. Lee
2. Jacob Devlin
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Christopher D. Manning
6. Sepp Hochreiter
7. Diederik P. Kingma
8. Ilya Sutskever
9. Jeffrey Pennington
10. Richard Socher

Who trusts Oshin Agarwal overall

1. Yang Trista Cao
2. Boshi Wang
3. Daniel Loureiro
4. Hal Daumé Iii
5. Pierre L. Dognin
6. Md. Rashad Al Hasan Rony
7. Shayne Longpre
8. Chenguang Wang
9. Barlas Oğuz
10. Xiao Liu

Papers from Oshin Agarwal's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. ImageNet: A large-scale hierarchical image database
9. Gradient-based learning applied to document recognition
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training (2021) — 208 citations
• Word Embeddings (Also) Encode Human Personality Stereotypes (2019) — 19 citations
• Temporal Effects on Pre-trained Models for Language Processing Tasks (2021) — 72 citations
• Large Scale Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training (2020) — 36 citations
• Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models (2020) — 24 citations
• Evaluation of named entity coreference (2019) — 16 citations