Danqing Wang

Natural Language Processing · with Chen · 2019–2021

A researcher in the Science corpus: 4 papers; trusts 124 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 111 citations into it; #2,783 of 5,688 by trust here, #3,014 by citations
• Artificial Intelligence — 106 citations into it; #13,543 of 35,345 by trust here, #11,921 by citations
• Computer Vision and Pattern Recognition — 30 citations into it
• Evaluation & Benchmarks — 17 citations into it
• Model Architectures — 13 citations into it
• Large Language Models — 10 citations into it
• General Social Sciences — 8 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Danqing Wang trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Yann LeCun
5. Sepp Hochreiter
6. Yang Liu
7. Mirella Lapata
8. Chin-Yew Lin
9. Richard Socher
10. Ilya Sutskever

Who trusts Danqing Wang overall

1. Ming Zhong
2. Pengfei Liu
3. Yixin Liu
4. Richard Yuanzhe Pang
5. Congbo Ma
6. Yiran Chen
7. Xipeng Qiu
8. Pierre Colombo
9. Zi-Yi Dou
10. Á. Lelkes

Papers from Danqing Wang's perspective

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

Their papers

• Extractive Summarization as Text Matching (2020) — 521 citations
• Searching for Effective Neural Extractive Summarization: What Works and What’s Next (2019) — 161 citations
• Heterogeneous Graph Neural Networks for Extractive Document Summarization (2020) — 300 citations
• MTG: A Benchmark Suite for Multilingual Text Generation (2021) — 26 citations