Satoshi Sekine
Natural Language Processing · 2002–2019
A researcher in the Science corpus: 8 papers; trusts 66 researchers and is trusted by 54 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 80 citations into it; #3,701 of 5,688 by trust here, #3,190 by citations
- Artificial Intelligence — 77 citations into it; #4,218 of 35,345 by trust here, #5,120 by citations
- Evaluation & Benchmarks — 35 citations into it
- Computer Vision and Pattern Recognition — 27 citations into it; #14,561 of 21,575 by trust here, #10,334 by citations
- Information Extraction — 11 citations into it
- Information Retrieval & Search — 9 citations into it
Whom Satoshi Sekine trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Dekang Lin
- Michael Collins
- Eugene Charniak
- Peter D. Turney
- Marti A. Hearst
- Burr Settles
- Andrew McCallum
- Yoshua Bengio
- Eugene Agichtein
- Deepak Ravichandran
Who trusts Satoshi Sekine overall
- Jochen L. Leidner
- Stefan Harmeling
- Qian Chen
- Kiem-Hieu Nguyen
- Suyu Ge
- Yuan Luo
- Vikas Yadav
- Alisa Smirnova
- Arindam Mitra
- Fei Wu
Papers from Satoshi Sekine's perspective
Ordered by how strongly the researchers Satoshi Sekine trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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 Makes Reading Comprehension Questions Easier? (2018) — 127 citations
- A survey of named entity recognition and classification (2007) — 2,979 citations
- Preemptive Information Extraction using Unrestricted Relation Discovery (2006) — 292 citations
- Discovering Relations among Named Entities from Large Corpora (2004) — 485 citations
- Can Neural Networks Understand Monotonicity Reasoning? (2019) — 89 citations
- Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (2007) — 81 citations
- Extended Named Entity Hierarchy (2002) — 307 citations
- Semi-supervised Relation Extraction with Large-scale Word Clustering (2011) — 132 citations