Josef Valvoda

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 4 papers; trusts 19 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 64 citations into it; #14,780 of 35,345 by trust here, #12,244 by citations
• Natural Language Processing — 45 citations into it; #4,502 of 5,688 by trust here, #3,235 by citations
• Safety, Robustness & Interpretability — 16 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Evaluation & Benchmarks — 11 citations into it

Whom Josef Valvoda trusts overall

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

1. John Hewitt
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Jacob Devlin
7. Ilya Sutskever
8. Christopher D. Manning
9. Nitish Srivastava
10. Matthew E. Peters

Who trusts Josef Valvoda overall

1. Yonatan Belinkov
2. Tiago Pimentel
3. Mycal Tucker
4. Zining Zhu
5. Xikun Zhang
6. Yichu Zhou
7. J. O’Connor
8. Peng Qian
9. John Hewitt
10. Koustuv Sinha

Papers from Josef Valvoda's perspective

Ordered by how strongly the researchers Josef Valvoda 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. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Information-Theoretic Probing for Linguistic Structure (2020) — 280 citations
• A Tale of a Probe and a Parser (2020) — 63 citations
• On the Machine Learning of Ethical Judgments from Natural Language (2022) — 65 citations
• SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection (2020) — 90 citations