Stefan Schweter

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 4 papers; trusts 28 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 154 citations into it; #34,751 of 35,345 by trust here, #20,377 by citations
• Natural Language Processing — 112 citations into it; #5,571 of 5,688 by trust here, #4,183 by citations
• Large Language Models — 61 citations into it
• Evaluation & Benchmarks — 46 citations into it
• Safety, Robustness & Interpretability — 21 citations into it
• Hardware and Architecture — 6 citations into it

Whom Stefan Schweter trusts overall

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

1. Alan Akbik
2. Jörg Tiedemann
3. Jacob Devlin
4. Matthew E. Peters
5. Michael Wiegand
6. Jeremy Howard
7. Geoffrey E. Hinton
8. Ashish Vaswani
9. Yoshua Bengio
10. Diederik P. Kingma

Who trusts Stefan Schweter overall

1. Sebastian Riedel

Papers from Stefan Schweter's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
3. Long Short-Term Memory
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. ImageNet classification with deep convolutional neural networks
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. GloVe: Global Vectors for Word Representation
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

• FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP (2019) — 933 citations
• Entities, Dates, and Languages: Zero-Shot on Historical Texts with T0 (2022) — 11 citations
• German’s Next Language Model (2020) — 346 citations
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations