Weijie Liu

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 40 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 52 citations into it; #29,211 of 35,345 by trust here, #8,619 by citations
• Natural Language Processing — 47 citations into it
• Large Language Models — 26 citations into it; #611 of 799 by trust here, #621 by citations
• Computer Vision and Pattern Recognition — 17 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Evaluation & Benchmarks — 13 citations into it

Whom Weijie Liu trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Jacob Devlin
4. Diederik P. Kingma
5. Alec Radford
6. Alex Graves
7. Ilya Sutskever
8. Alex Krizhevsky
9. Yann LeCun
10. Ashish Vaswani

Who trusts Weijie Liu overall

1. Canwen Xu
2. Tal Schuster
3. Young Jin Kim
4. Tara Safavi
5. Wangchunshu Zhou
6. Julian McAuley
7. Ji Xin
8. Pengcheng Yin
9. Shijie Geng
10. Jianping Gou

Papers from Weijie Liu's perspective

Ordered by how strongly the researchers Weijie Liu 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. ImageNet: A large-scale hierarchical image database
8. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• K-BERT: Enabling Language Representation with Knowledge Graph (2019) — 930 citations
• Whitening Sentence Representations for Better Semantics and Faster Retrieval (2021) — 370 citations
• FastBERT: a Self-distilling BERT with Adaptive Inference Time (2020) — 436 citations