Buzhou Tang

Natural Language Processing · 2014–2018

A researcher in the Science corpus: 6 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 75 citations into it
• Artificial Intelligence — 58 citations into it
• Molecular Biology — 21 citations into it
• Evaluation & Benchmarks — 19 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Information Extraction — 7 citations into it
• Large Language Models — 7 citations into it

Whom Buzhou Tang trusts overall

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

1. Yoshua Bengio
2. Tomas Mikolov
3. Burr Settles
4. Andrew McCallum
5. Lawrence R. Rabiner
6. Geoffrey E. Hinton
7. Thomas Hofmann
8. C. Burges
9. Ronan Collobert
10. Joseph P. Turian

Who trusts Buzhou Tang overall

1. Shengyu Liu
2. Clayton A. Turner
3. Jinying Chen

Papers from Buzhou Tang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• The CHEMDNER corpus of chemicals and drugs and its annotation principles (2015) — 444 citations
• Effects of Semantic Features on Machine Learning-Based Drug Name Recognition Systems: Word Embeddings vs. Manually Constructed Dictionaries (2015) — 59 citations
• Evaluating Word Representation Features in Biomedical Named Entity Recognition Tasks (2014) — 133 citations
• LCQMC:A Large-scale Chinese Question Matching Corpus (2018) — 226 citations
• The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification (2018) — 118 citations
• A novel word embedding learning model using the dissociation between nouns and verbs (2016) — 26 citations