David Wadden
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 5 papers; trusts 57 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 95 citations into it; #13,067 of 35,345 by trust here, #6,796 by citations
- Natural Language Processing — 55 citations into it
- Evaluation & Benchmarks — 32 citations into it
- Molecular Biology — 32 citations into it
- Large Language Models — 29 citations into it
- Information Systems — 7 citations into it
- Sociology and Political Science — 6 citations into it
Whom David Wadden trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yi Luan
- Kenton C. T. Lee
- Matthew E. Peters
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Luheng He
- Iz Beltagy
- Makoto Miwa
- Ilya Sutskever
Who trusts David Wadden overall
- Sijia Wang
- Zexuan Zhong
- Markus Eberts
- Luyu Gao
- Sarah Wiegreffe
- Ying Lin
- Xinya Du
- Heng Ji
- Chenguang Wang
- Pengfei Yu
Papers from David Wadden's perspective
Ordered by how strongly the researchers David Wadden trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Fact or Fiction: Verifying Scientific Claims (2020) — 755 citations
- Entity, Relation, and Event Extraction with Contextualized Span Representations (2019) — 684 citations
- A general framework for information extraction using dynamic span graphs (2019) — 342 citations
- How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources (2023) — 510 citations
- A Next Generation Connectivity Map: L1000 platform and the first 1,000,000 profiles (2017) — 2,985 citations