Sabrina J. Mielke

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 8 papers; trusts 104 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 245 citations into it; #10,381 of 35,345 by trust here, #9,557 by citations
• Natural Language Processing — 186 citations into it; #2,246 of 5,688 by trust here, #2,132 by citations
• Large Language Models — 72 citations into it
• Computer Vision and Pattern Recognition — 70 citations into it; #12,256 of 21,575 by trust here, #19,310 by citations
• Model Architectures — 32 citations into it
• Optimization & Training — 12 citations into it
• Generative Models — 6 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Sabrina J. Mielke trusts overall

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

1. Yoshua Bengio
2. Ilya Sutskever
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Alex Graves
6. Tomas Mikolov
7. Alex Krizhevsky
8. Yee Whye Teh
9. Yann LeCun
10. J. Urgen Schmidhuber

Who trusts Sabrina J. Mielke overall

1. Alexandra Chronopoulou
2. Yang Trista Cao
3. Dian Yu
4. Ran Zmigrod
5. Zhen Lin
6. Oleh Shliazhko
7. Nouha Dziri
8. Nizar Habash
9. Christos Baziotis
10. Emily Dinan

Papers from Sabrina J. Mielke's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology (2019) — 344 citations
• Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP (2021) — 222 citations
• Are All Languages Equally Hard to Language-Model? (2018) — 116 citations
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations
• Linguistic calibration through metacognition: aligning dialogue agent responses with expected correctness (2020) — 26 citations
• SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection (2020) — 90 citations
• Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset (2020) — 94 citations
• Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model (2018) — 34 citations