Chengqing Zong
Artificial Intelligence · 2011–2020
A researcher in the Science corpus: 15 papers; trusts 584 researchers and is trusted by 48 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 274 citations into it; #5,322 of 35,345 by trust here, #6,848 by citations
- Natural Language Processing — 189 citations into it; #1,253 of 5,688 by trust here, #1,721 by citations
- Computer Vision and Pattern Recognition — 104 citations into it; #5,136 of 21,575 by trust here, #7,750 by citations
- Model Architectures — 43 citations into it
- Representation & Self-Supervised Learning — 42 citations into it
- Evaluation & Benchmarks — 26 citations into it
- Optimization & Training — 20 citations into it
- Reinforcement Learning — 20 citations into it
Whom Chengqing Zong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Diederik P. Kingma
- Geoffrey E. Hinton
- Ilya Sutskever
- Alex Krizhevsky
- Alex Graves
- Richard Socher
- Yann LeCun
- Kaiming He
- J. Urgen Schmidhuber
Who trusts Chengqing Zong overall
- Lijun Wu
- Yong Cheng
- Chenhui Chu
- Jiatao Gu
- Peng-Jen Chen
- Shuhao Gu
- Vishal. A. Kharde
- Surangika Ranathunga
- Felix Stahlberg
- Yu Li
Papers from Chengqing Zong's perspective
Ordered by how strongly the researchers Chengqing Zong 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Exploiting Source-side Monolingual Data in Neural Machine Translation (2016) — 297 citations
- Bilingually-constrained Phrase Embeddings for Machine Translation (2014) — 120 citations
- Three Strategies to Improve One-to-Many Multilingual Translation (2018) — 78 citations
- NCLS: Neural Cross-Lingual Summarization (2019) — 145 citations
- Synchronous Speech Recognition and Speech-to-Text Translation with Interactive Decoding (2019) — 73 citations
- Abstractive Cross-Language Summarization via Translation Model Enhanced Predicate Argument Structure Fusing (2016) — 70 citations
- Distill and Replay for Continual Language Learning (2020) — 41 citations
- Incremental Learning from Scratch for Task-Oriented Dialogue Systems (2019) — 23 citations
- MSMO: Multimodal Summarization with Multimodal Output (2018) — 196 citations
- Ensure the Correctness of the Summary: Incorporate Entailment Knowledge into Abstractive Sentence Summarization (2018) — 104 citations
- Associative Multichannel Autoencoder for Multimodal Word Representation (2018) — 26 citations
- A Teacher-Student Framework for Maintainable Dialog Manager (2018) — 7 citations
- Memory, Show the Way: Memory Based Few Shot Word Representation Learning (2018) — 16 citations
- Shortcut Sequence Tagging (2017)
- Ensemble of feature sets and classification algorithms for sentiment classification (2011) — 640 citations