Djamé Seddah
Natural Language Processing · 2010–2020
A researcher in the Science corpus: 6 papers; trusts 82 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 102 citations into it; #4,445 of 5,688 by trust here, #1,813 by citations
- Artificial Intelligence — 97 citations into it; #12,645 of 35,345 by trust here, #6,157 by citations
- Computer Vision and Pattern Recognition — 35 citations into it; #9,034 of 21,575 by trust here, #6,089 by citations
- Evaluation & Benchmarks — 26 citations into it
- Representation & Self-Supervised Learning — 23 citations into it
- Large Language Models — 16 citations into it; #263 of 799 by trust here, #423 by citations
Whom Djamé Seddah trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Michael Collins
- Diederik P. Kingma
- Yoshua Bengio
- Anne Abeillé
- Alexis Conneau
- Ilya Sutskever
- Christopher D. Manning
- Peter F. Brown
- Sabine Buchholz
Who trusts Djamé Seddah overall
- Mitchell Stern
- André F. T. Martins
- Liane Guillou
- Koustuv Sinha
- Ondrej Bojar
- Jacob Andreas
- Yada Pruksachatkun
- Ramón Fernandez Astudillo
- Daniel Klein
- Gabriel Ilharco
Papers from Djamé Seddah's perspective
Ordered by how strongly the researchers Djamé Seddah 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- What Does BERT Learn about the Structure of Language? (2019) — 1,594 citations
- CamemBERT: a Tasty French Language Model (2019) — 1,110 citations
- Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering (2020) — 62 citations
- Universal Dependencies 2.1 (2017) — 425 citations
- Introducing the SPMRL 2014 Shared Task on Parsing Morphologically-rich Languages (2014) — 111 citations
- Statistical Parsing of Morphologically Rich Languages (SPMRL) What, How and Whither (2010) — 151 citations