Bernd Bohnet

Artificial Intelligence · with Mille · 2010–2022

A researcher in the Science corpus: 9 papers; trusts 166 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 128 citations into it; #10,116 of 35,345 by trust here, #5,120 by citations
• Natural Language Processing — 120 citations into it; #1,976 of 5,688 by trust here, #1,274 by citations
• Evaluation & Benchmarks — 37 citations into it; #1,238 of 3,147 by trust here, #865 by citations
• Computer Vision and Pattern Recognition — 29 citations into it
• Large Language Models — 23 citations into it
• Model Architectures — 10 citations into it

Whom Bernd Bohnet trusts overall

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

1. Ryan T. McDonald
2. Michael Collins
3. Avrim Blum
4. Koby Crammer
5. Ivan Titov
6. Geoffrey E. Hinton
7. Ali Rahimi
8. Fernando C Pereira
9. Yoshua Bengio
10. Ilya Sutskever

Who trusts Bernd Bohnet overall

1. Kevin Gimpel
2. Michael Roth
3. Anders Björkelund
4. Ondrej Dusek
5. Marion Weller
6. Noah A. Smith
7. Jörg Tiedemann
8. Mirella Lapata
9. Albert Gatt
10. Jonas Kuhn

Papers from Bernd Bohnet's perspective

Ordered by how strongly the researchers Bernd Bohnet 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. Attention is All you Need (Neural Information Processing Systems)
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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• On Faithfulness and Factuality in Abstractive Summarization (2020) — 1,585 citations
• The First Multilingual Surface Realisation Shared Task (SR’18): Overview and Evaluation Results (2018) — 65 citations
• Honest Students from Untrusted Teachers: Learning an Interpretable Question-Answering Pipeline from a Pretrained Language Model (2022) — 27 citations
• The Third Multilingual Surface Realisation Shared Task (SR’20): Overview and Evaluation Results (2020)
• Named Entity Recognition as Dependency Parsing (2020) — 501 citations
• Proceedings of the 2nd Workshop on Multilingual Surface Realisation (MSR 2019) (2019)
• A High-Performance Syntactic and Semantic Dependency Parser (2010) — 182 citations
• Top Accuracy and Fast Dependency Parsing is not a Contradiction (2010) — 389 citations
• Broad Coverage Multilingual Deep Sentence Generation with a Stochastic Multi-Level Realizer (2010) — 61 citations