Thomas Davidson

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 24 researchers and is trusted by 95 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it; #2,655 of 35,345 by trust here, #2,584 by citations
• Natural Language Processing — 40 citations into it; #672 of 5,688 by trust here, #614 by citations
• Safety, Robustness & Interpretability — 31 citations into it; #219 of 2,251 by trust here, #234 by citations
• Information Systems — 20 citations into it; #532 of 8,771 by trust here, #332 by citations
• Communication — 12 citations into it
• AI Ethics, Fairness & Society — 7 citations into it; #20 of 494 by trust here, #8 by citations
• Sociology and Political Science — 7 citations into it
• Law — 6 citations into it

Whom Thomas Davidson trusts overall

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

1. Zeerak Talat
2. Su Lin Blodgett
3. P. Burnap
4. Michael Elhadad
5. Dirk Hovy
6. Gary King
7. Leandro Araújo Silva
8. Irene Kwok
9. Clayton J. Hutto
10. Nemanja Djuric

Who trusts Thomas Davidson overall

1. Bertie Vidgen
2. Svetlana Kiritchenko
3. Maarten Sap
4. Isar Nejadgholi
5. Mladen Karan
6. Marcos Zampieri
7. Shervin Malmasi
8. Zeerak Talat
9. Valerio Basile
10. Alexandra Olteanu

Papers from Thomas Davidson's perspective

Ordered by how strongly the researchers Thomas Davidson 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. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
4. Efficient Estimation of Word Representations in Vector Space
5. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. ImageNet classification with deep convolutional neural networks
8. Locate the Hate: Detecting Tweets against Blacks
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. Detecting Hate Speech on the World Wide Web

Their papers

• Automated Hate Speech Detection and the Problem of Offensive Language (2017) — 3,212 citations
• Racial Bias in Hate Speech and Abusive Language Detection Datasets (2019) — 530 citations
• Understanding Abuse: A Typology of Abusive Language Detection Subtasks (2017) — 524 citations