Song Wang
Information Systems · with Liu · 2016–2023
A researcher in the Science corpus: 3 papers; trusts 38 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 83 citations into it; #1,980 of 8,771 by trust here, #1,964 by citations
- Software — 66 citations into it; #270 of 1,227 by trust here, #236 by citations
- Artificial Intelligence — 40 citations into it
- Natural Language Processing — 20 citations into it; #4,666 of 5,688 by trust here, #4,682 by citations
- Code Generation & Program Synthesis — 19 citations into it
- Computer Networks and Communications — 19 citations into it
- Signal Processing — 18 citations into it; #3,064 of 7,572 by trust here, #2,816 by citations
- Computer Vision and Pattern Recognition — 7 citations into it
Whom Song Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Premkumar T. Devanbu
- Yoshua Bengio
- Geoffrey E. Hinton
- Ahmed E. Hassan
- Gonzalo Navarro
- R. Rosenfeld
- Thomas Zimmermann
- Mauricio A. Saca
- David M. Blei
- Tung Thanh Nguyen
Who trusts Song Wang overall
- Xi Victoria Lin
- Michael Pradel
- Yi Li
- Vijayaraghavan Murali
- Rabee Sohail Malik
- Jin L.C. Guo
- Shaohua Wang
- Thibaud Lutellier
- Guanjun Lin
- Yu Wang
Papers from Song Wang's perspective
Ordered by how strongly the researchers Song Wang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Software Testing With Large Language Models: Survey, Landscape, and Vision (2023) — 664 citations
- Automatically Learning Semantic Features for Defect Prediction (2016) — 723 citations
- Bugram: Bug detection with n-gram language models (2016) — 146 citations