Nora Kassner

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 10 papers; trusts 303 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 360 citations into it; #4,579 of 35,345 by trust here, #6,517 by citations
• Natural Language Processing — 255 citations into it; #1,145 of 5,688 by trust here, #1,779 by citations
• Large Language Models — 121 citations into it; #286 of 799 by trust here, #307 by citations
• Computer Vision and Pattern Recognition — 97 citations into it; #4,842 of 21,575 by trust here, #6,031 by citations
• Evaluation & Benchmarks — 90 citations into it; #819 of 3,147 by trust here, #1,728 by citations
• Safety, Robustness & Interpretability — 44 citations into it
• Representation & Self-Supervised Learning — 30 citations into it
• Information Retrieval & Search — 21 citations into it; #721 of 1,022 by trust here, #886 by citations

Whom Nora Kassner trusts overall

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

1. Geoffrey E. Hinton
2. Jacob Devlin
3. Yoshua Bengio
4. Diederik P. Kingma
5. Ilya Sutskever
6. Alex Krizhevsky
7. Yann LeCun
8. Kaiming He
9. Fabio Petroni
10. Jason Aaron Edward Weston

Who trusts Nora Kassner overall

1. Yanai Elazar
2. Gregor Betz
3. Abhilasha Ravichander
4. Katikapalli Subramanyam Kalyan
5. Kyle Richardson
6. Tara Safavi
7. Priyanka Sen
8. Badr AlKhamissi
9. Yichu Zhou
10. Hinrich Schütze

Papers from Nora Kassner's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. ImageNet: A large-scale hierarchical image database
8. Gradient-based learning applied to document recognition
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

• Measuring and Improving Consistency in Pretrained Language Models (2021) — 487 citations
• Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly (2019) — 382 citations
• BeliefBank: Adding Memory to a Pre-Trained Language Model for a Systematic Notion of Belief (2021) — 74 citations
• Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models (2021) — 167 citations
• Are Pretrained Language Models Symbolic Reasoners over Knowledge? (2020) — 79 citations
• Measuring Causal Effects of Data Statistics on Language Model's 'Factual' Predictions (2022) — 67 citations
• Enriching a Model's Notion of Belief using a Persistent Memory (2021) — 7 citations
• BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA (2020) — 72 citations
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations
• Negated LAMA: Birds cannot fly (2019) — 23 citations