Leo Wanner

Natural Language Processing · 2010–2020

A researcher in the Science corpus: 9 papers; trusts 44 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 48 citations into it; #3,506 of 5,688 by trust here, #3,421 by citations
• Artificial Intelligence — 46 citations into it; #25,875 of 35,345 by trust here, #22,463 by citations
• Evaluation & Benchmarks — 15 citations into it
• Information Systems — 8 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Safety, Robustness & Interpretability — 5 citations into it

Whom Leo Wanner trusts overall

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

1. Minqing Hu
2. Arjun Mukherjee
3. Moshe Koppel
4. Mihai Surdeanu
5. Shlomo Engelson Argamon
6. Jonathan Schler
7. Richard Johansson
8. Sandra A. Thompson
9. Martha Palmer
10. Anya Belz

Who trusts Leo Wanner overall

1. Ondrej Dusek
2. Albert Gatt
3. Yang Trista Cao
4. Anya Belz

Papers from Leo Wanner's perspective

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

1. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
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. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. GloVe: Global Vectors for Word Representation
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Language Models are Unsupervised Multitask Learners
10. Gradient-based learning applied to document recognition

Their papers

• The First Multilingual Surface Realisation Shared Task (SR’18): Overview and Evaluation Results (2018) — 65 citations
• FORGe at SemEval-2017 Task 9: Deep sentence generation based on a sequence of graph transducers (2017) — 24 citations
• The Third Multilingual Surface Realisation Shared Task (SR’20): Overview and Evaluation Results (2020)
• Toxic, Hateful, Offensive or Abusive? What Are We Really Classifying? An Empirical Analysis of Hate Speech Datasets (2020) — 184 citations
• Proceedings of the 2nd Workshop on Multilingual Surface Realisation (MSR 2019) (2019)
• On the Relevance of Syntactic and Discourse Features for Author Profiling and Identification (2017) — 32 citations
• How to Use less Features and Reach Better Performance in Author Gender Identification (2014) — 24 citations
• Overview of the First Content Selection Challenge from Open Semantic Web Data (2013) — 8 citations
• Broad Coverage Multilingual Deep Sentence Generation with a Stochastic Multi-Level Realizer (2010) — 61 citations