Abeba Birhane
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 10 papers; trusts 307 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 334 citations into it
- Safety, Robustness & Interpretability — 186 citations into it; #862 of 2,251 by trust here, #247 by citations
- Natural Language Processing — 158 citations into it
- Computer Vision and Pattern Recognition — 136 citations into it; #6,644 of 21,575 by trust here, #5,941 by citations
- Sociology and Political Science — 97 citations into it
- Safety Research — 86 citations into it; #683 of 5,829 by trust here, #468 by citations
- Evaluation & Benchmarks — 83 citations into it; #1,052 of 3,147 by trust here, #1,856 by citations
- AI Ethics, Fairness & Society — 75 citations into it
Whom Abeba Birhane trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Yoshua Bengio
- Jia Deng
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Karen Simonyan
- Ruslan Salakhutdinov
Who trusts Abeba Birhane overall
- Stella Biderman
- Patrick Schramowski
- Inioluwa Deborah Raji
- Yacine Jernite
- Angelina Wang
- Steven Bird
- Pratyusha Kalluri
- Luming Tang
- Florian Tramèr
- Ben Hutchinson
Papers from Abeba Birhane's perspective
Ordered by how strongly the researchers Abeba Birhane trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Ethical and social risks of harm from Language Models (2021) — 1,580 citations
- Multimodal datasets: misogyny, pornography, and malignant stereotypes (2021) — 486 citations
- Large image datasets: A pyrrhic win for computer vision? (2020) — 434 citations
- Taxonomy of Risks posed by Language Models (2022) — 1,066 citations
- The Values Encoded in Machine Learning Research (2021) — 401 citations
- Power to the People? Opportunities and Challenges for Participatory AI (2022) — 422 citations
- The Forgotten Margins of AI Ethics (2022) — 144 citations
- Algorithmic injustice: a relational ethics approach (2021) — 540 citations
- Algorithmic Colonization of Africa (2020) — 246 citations
- Conversational AI: Social and Ethical Considerations (2019) — 114 citations