Danqing Huang
Natural Language Processing · 2016–2018
A researcher in the Science corpus: 4 papers; trusts 75 researchers and is trusted by 36 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 77 citations into it; #1,238 of 5,688 by trust here, #1,837 by citations
- Artificial Intelligence — 74 citations into it; #7,117 of 35,345 by trust here, #9,557 by citations
- Information Systems — 15 citations into it; #3,799 of 8,771 by trust here, #2,471 by citations
- Computer Vision and Pattern Recognition — 14 citations into it; #9,254 of 21,575 by trust here, #11,721 by citations
- Computational Theory and Mathematics — 10 citations into it
- Reinforcement Learning — 9 citations into it
- Prompting & Reasoning — 6 citations into it
- Evaluation & Benchmarks — 5 citations into it; #1,699 of 3,147 by trust here, #1,876 by citations
Whom Danqing Huang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Shuming Shi
- Yefim Bakman
- Yoshua Bengio
- Dzmitry Bahdanau
- Ilya Sutskever
- Geoffrey E. Hinton
- Subhro Roy
- Nate Kushman
- Chin-Yew Lin
- Diederik P. Kingma
Who trusts Danqing Huang overall
- Lei Wang
- Dongxiang Zhang
- Jinghui Qin
- Jierui Li
- Jipeng Zhang
- Yining Hong
- Bugeun Kim
- Yan Wang
- Zhenwen Liang
- Xiaodan Liang
Papers from Danqing Huang's perspective
Ordered by how strongly the researchers Danqing Huang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- How well do Computers Solve Math Word Problems? Large-Scale Dataset Construction and Evaluation (2016) — 159 citations
- Learning Fine-Grained Expressions to Solve Math Word Problems (2017) — 91 citations
- Using Intermediate Representations to Solve Math Word Problems (2018) — 29 citations
- Neural Math Word Problem Solver with Reinforcement Learning (2018) — 91 citations