Jinho D. Choi
Natural Language Processing · 2013–2021
A researcher in the Science corpus: 5 papers; trusts 93 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 115 citations into it; #3,137 of 5,688 by trust here, #3,574 by citations
- Artificial Intelligence — 110 citations into it; #18,022 of 35,345 by trust here, #17,776 by citations
- Computer Vision and Pattern Recognition — 29 citations into it; #11,424 of 21,575 by trust here, #12,172 by citations
- Evaluation & Benchmarks — 20 citations into it; #1,675 of 3,147 by trust here, #2,799 by citations
- Model Architectures — 12 citations into it
- Information Retrieval & Search — 8 citations into it
- Large Language Models — 8 citations into it
Whom Jinho D. Choi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Christopher D. Manning
- Alec Radford
- Ilya Sutskever
- Diederik P. Kingma
- Tomas Mikolov
- Alex Krizhevsky
- Jacob Devlin
- Richard Socher
Who trusts Jinho D. Choi overall
Papers from Jinho D. Choi's perspective
Ordered by how strongly the researchers Jinho D. Choi trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Analysis of Wikipedia-based Corpora for Question Answering (2018) — 6 citations
- NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2021) — 104 citations
- SelQA: A New Benchmark for Selection-Based Question Answering (2016) — 42 citations
- Establishing Strong Baselines for the New Decade: Sequence Tagging, Syntactic and Semantic Parsing with BERT (2019) — 51 citations
- Dynamic Knowledge-Base Alignment for Coreference Resolution (2013) — 30 citations