Michael Völske

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it; #12,914 of 35,345 by trust here, #17,776 by citations
• Natural Language Processing — 16 citations into it; #2,439 of 5,688 by trust here, #3,574 by citations
• Evaluation & Benchmarks — 6 citations into it

Whom Michael Völske trusts overall

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

1. Alexander M. Rush
2. Baotian Hu
3. Rasim M. Alguliyev
4. Sumit Chopra
5. Chin-Yew Lin
6. Ju-hong Lee
7. Ramesh Nallapati
8. Hoa Trang Dang
9. Jason Aaron Edward Weston
10. Ani Nenkova

Who trusts Michael Völske overall

1. J'er'emy Scheurer
2. Jon Ander Campos
3. Adam Gleave
4. Akash Kumar Mohankumar
5. Sebastian Gehrmann
6. Yao Zhao
7. Nisan Stiennon
8. Jun Shern Chan
9. Jingqing Zhang
10. Daniel M. Ziegler

Papers from Michael Völske's perspective

Ordered by how strongly the researchers Michael Völske 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Attention is All you Need (Neural Information Processing Systems)
4. Long Short-Term Memory
5. ImageNet classification with deep convolutional neural networks
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
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. ROUGE: A Package for Automatic Evaluation of Summaries
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• TL;DR: Mining Reddit to Learn Automatic Summarization (2017) — 274 citations
• Towards Summarization for Social Media - Results of the TL;DR Challenge (2019) — 7 citations