Andrew Zaldivar

Artificial Intelligence · with Barnes · 2018–2022

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

Subfields

• Artificial Intelligence — 17 citations into it; #32,081 of 35,345 by trust here, #3,715 by citations
• Evaluation & Benchmarks — 10 citations into it
• Safety Research — 9 citations into it; #4,868 of 5,829 by trust here, #161 by citations
• Natural Language Processing — 5 citations into it

Whom Andrew Zaldivar trusts overall

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

1. Emily M. Bender
2. Batya Friedman
3. Michael Hind

Who trusts Andrew Zaldivar overall

1. Sebastian Gehrmann
2. Inioluwa Deborah Raji
3. Irene Solaiman
4. Daniel S. Schiff

Papers from Andrew Zaldivar's perspective

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

1. Deep Learning Face Attributes in the Wild
2. Bleu: a Method for Automatic Evaluation of Machine Translation
3. Equality of Opportunity in Supervised Learning
4. Datasheets for datasets
5. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
6. ImageNet classification with deep convolutional neural networks
7. Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments
8. The Dataset Nutrition Label: A Framework To Drive Higher Data Quality Standards
9. Data Statements for NLP: Toward Mitigating System Bias and Enabling Better Science
10. Measuring and Mitigating Unintended Bias in Text Classification

Their papers

• Model Cards for Model Reporting (2018) — 2,935 citations
• Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI (2022) — 352 citations