Donghong Ji

Artificial Intelligence · 2006–2021

A researcher in the Science corpus: 7 papers; trusts 99 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 100 citations into it; #30,794 of 35,345 by trust here, #16,166 by citations
• Natural Language Processing — 61 citations into it
• Molecular Biology — 27 citations into it; #14,003 of 17,773 by trust here, #11,608 by citations
• Model Architectures — 17 citations into it
• Information Extraction — 13 citations into it; #260 of 407 by trust here, #250 by citations
• Computer Vision and Pattern Recognition — 11 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Management Science and Operations Research — 9 citations into it

Whom Donghong Ji trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Christopher D. Manning
5. Eugene Charniak
6. Ilya Sutskever
7. Alex Krizhevsky
8. Jimmy Ba
9. Yann LeCun
10. Yoon Kim

Who trusts Donghong Ji overall

1. Thien Huu Nguyen
2. Ralph Grishman

Papers from Donghong Ji's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Long Short-Term Memory
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet classification with deep convolutional neural networks
6. Gradient-based learning applied to document recognition
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• A neural joint model for entity and relation extraction from biomedical text (2017) — 249 citations
• The CHEMDNER corpus of chemicals and drugs and its annotation principles (2015) — 444 citations
• Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification (2020) — 387 citations
• Unified Named Entity Recognition as Word-Word Relation Classification (2021) — 351 citations
• Joint Models for Extracting Adverse Drug Events from Biomedical Text (2016) — 60 citations
• Tree Kernel-Based Relation Extraction with Context-Sensitive Structured Parse Tree Information (2007) — 221 citations
• Relation Extraction Using Label Propagation Based Semi-Supervised Learning (2006) — 114 citations