Benjamin Schiller

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 30 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it; #23,369 of 35,345 by trust here, #13,760 by citations
• Natural Language Processing — 38 citations into it; #3,921 of 5,688 by trust here, #2,930 by citations
• Evaluation & Benchmarks — 9 citations into it
• Model Architectures — 9 citations into it

Whom Benjamin Schiller trusts overall

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

1. Chin-Yew Lin
2. Yoshua Bengio
3. Ilya Sutskever
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Jacob Devlin
7. Alon Lavie
8. Ashish Vaswani
9. Richard Socher
10. Christian Stab

Who trusts Benjamin Schiller overall

1. Alexis Ross
2. Shuohuan Wang
3. James Thorne
4. Tongshuang Sherry Wu

Papers from Benjamin Schiller's perspective

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

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

• UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification (2018) — 206 citations
• Cross-topic Argument Mining from Heterogeneous Sources (2018) — 219 citations
• Aspect-Controlled Neural Argument Generation (2020) — 85 citations