Lucy Vasserman
Artificial Intelligence · 2018–2022
A researcher in the Science corpus: 5 papers; trusts 17 researchers and is trusted by 42 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 60 citations into it; #5,418 of 35,345 by trust here, #2,050 by citations
- Safety, Robustness & Interpretability — 41 citations into it; #570 of 2,251 by trust here, #181 by citations
- Natural Language Processing — 34 citations into it; #2,203 of 5,688 by trust here, #1,407 by citations
- Safety Research — 14 citations into it; #1,890 of 5,829 by trust here, #118 by citations
- Evaluation & Benchmarks — 12 citations into it; #2,138 of 3,147 by trust here, #1,467 by citations
- Information Systems — 11 citations into it
- Communication — 9 citations into it
- Statistics and Probability — 6 citations into it
Whom Lucy Vasserman trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Lucy Vasserman overall
- Svetlana Kiritchenko
- Oguzhan Gencoglu
- Debora Nozza
- Anthony Rios
- Sunipa Dev
- Ben Hutchinson
- Kawin Ethayarajh
- Yi Tay
Papers from Lucy Vasserman's perspective
Ordered by how strongly the researchers Lucy Vasserman trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Bleu: a Method for Automatic Evaluation of Machine Translation
- Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
- Equality of Opportunity in Supervised Learning
- Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
- Deep Learning Face Attributes in the Wild
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Their papers
- Model Cards for Model Reporting (2018) — 2,935 citations
- Measuring and Mitigating Unintended Bias in Text Classification (2018) — 916 citations
- Is Your Toxicity My Toxicity? Exploring the Impact of Rater Identity on Toxicity Annotation (2022) — 136 citations
- Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification (2019) — 607 citations
- A New Generation of Perspective API: Efficient Multilingual Character-level Transformers (2022) — 306 citations