Daxiang Dong

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 4 papers; trusts 38 researchers and is trusted by 42 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it; #5,800 of 35,345 by trust here, #3,757 by citations
• Natural Language Processing — 68 citations into it; #1,673 of 5,688 by trust here, #1,546 by citations
• Computer Vision and Pattern Recognition — 35 citations into it; #5,895 of 21,575 by trust here, #3,459 by citations
• Information Retrieval & Search — 29 citations into it; #775 of 1,022 by trust here, #319 by citations
• Evaluation & Benchmarks — 12 citations into it
• Model Architectures — 12 citations into it
• Optimization & Training — 7 citations into it

Whom Daxiang Dong trusts overall

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

1. L. Eon Bottou
2. Yoshua Bengio
3. Matthew D. Zeiler
4. Kyunghyun Cho
5. Geoffrey E. Hinton
6. Dzmitry Bahdanau
7. Philipp Koehn
8. Ilya Sutskever
9. Yann LeCun
10. Oriol Vinyals

Who trusts Daxiang Dong overall

1. Carlos Escolano
2. Minh-Thang Luong
3. Orhan Firat
4. Felix Stahlberg
5. Graham Neubig
6. Raj Dabre
7. Marta Ruiz Costa-jussà
8. Barret Zoph
9. Yuta Nishimura
10. Kyunghyun Cho

Papers from Daxiang Dong's perspective

Ordered by how strongly the researchers Daxiang Dong 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. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. 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

• Multi-Task Learning for Multiple Language Translation (2015) — 653 citations
• RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering (2020) — 749 citations
• Multi-view Response Selection for Human-Computer Conversation (2016) — 233 citations
• Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network (2018) — 349 citations