Bingquan Liu
Natural Language Processing · 2017–2020
A researcher in the Science corpus: 4 papers; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 71 citations into it
- Artificial Intelligence — 69 citations into it
- Computer Vision and Pattern Recognition — 24 citations into it
- Information Retrieval & Search — 12 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
Whom Bingquan Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Oriol Vinyals
- Ilya Sutskever
- Quoc V. Le
- Yoshua Bengio
- Jiwei Li
- Diederik P. Kingma
- Geoffrey E. Hinton
- Tomas Mikolov
- Kyunghyun Cho
- Alex Krizhevsky
Who trusts Bingquan Liu overall
Papers from Bingquan Liu's perspective
Ordered by how strongly the researchers Bingquan Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- GENERATIVE ADVERSARIAL NETS
Their papers
- Neural Response Generation via GAN with an Approximate Embedding Layer (2017) — 86 citations
- LSDSCC: a Large Scale Domain-Specific Conversational Corpus for Response Generation with Diversity Oriented Evaluation Metrics (2018) — 14 citations
- HopRetriever: Retrieve Hops over Wikipedia to Answer Complex Questions (2020) — 36 citations
- ITNLP-AiKF at SemEval-2017 Task 1: Rich Features Based SVR for Semantic Textual Similarity Computing (2017) — 3 citations