Lu Wang
Artificial Intelligence · with Cao · 2019–2021
A researcher in the Science corpus: 4 papers; trusts 384 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 138 citations into it; #14,742 of 35,345 by trust here, #10,798 by citations
- Natural Language Processing — 124 citations into it; #2,712 of 5,688 by trust here, #2,364 by citations
- Computer Vision and Pattern Recognition — 32 citations into it
- Evaluation & Benchmarks — 30 citations into it; #1,774 of 3,147 by trust here, #2,275 by citations
- Model Architectures — 18 citations into it
- Large Language Models — 14 citations into it
- Representation & Self-Supervised Learning — 12 citations into it
- Molecular Biology — 11 citations into it
Whom Lu Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Ilya Sutskever
- Diederik P. Kingma
- Alex Krizhevsky
- Kyunghyun Cho
- Yann LeCun
- Kaiming He
- Dzmitry Bahdanau
- Christopher D. Manning
Who trusts Lu Wang overall
Papers from Lu Wang's perspective
Ordered by how strongly the researchers Lu Wang trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- 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
Their papers
- BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization (2019) — 272 citations
- Efficient Attentions for Long Document Summarization (2021) — 442 citations
- CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization (2021) — 212 citations
- Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward (2020) — 173 citations