Yang Trista Cao

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 5 papers; trusts 205 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 263 citations into it; #23,381 of 35,345 by trust here, #10,942 by citations
• Natural Language Processing — 195 citations into it; #4,383 of 5,688 by trust here, #2,634 by citations
• Safety, Robustness & Interpretability — 87 citations into it
• Gender Studies — 47 citations into it
• Evaluation & Benchmarks — 41 citations into it
• Sociology and Political Science — 40 citations into it
• Human-Computer Interaction — 37 citations into it
• Computational Linguistics & Semantics — 32 citations into it

Whom Yang Trista Cao trusts overall

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

1. Vincent Ng
2. Lauren Ackerman
3. Rachel Rudinger
4. Geoffrey E. Hinton
5. Jieyu Zhao
6. Shane Bergsma
7. Yoshua Bengio
8. Christopher D. Manning
9. Diederik P. Kingma
10. Ilya Sutskever

Who trusts Yang Trista Cao overall

1. Sunipa Dev
2. Oskar van der Wal
3. Jesse Vig
4. Saghar Hosseini
5. Dominik Bachmann
6. Sebastian Gehrmann
7. Karolina Stańczak
8. Omar Shaikh
9. Emily Sheng
10. Connor Baumler

Papers from Yang Trista Cao's perspective

Ordered by how strongly the researchers Yang Trista Cao 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. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Gradient-based learning applied to document recognition

Their papers

• Analyzing Stereotypes in Generative Text Inference Tasks (2021) — 22 citations
• Toward Gender-Inclusive Coreference Resolution (2019) — 158 citations
• Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning Lifecycle* (2021) — 63 citations
• On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations (2022) — 112 citations
• Theory-Grounded Measurement of U.S. Social Stereotypes in English Language Models (2022) — 63 citations