Lin-Jun Yang

Artificial Intelligence · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 82 citations into it; #28,526 of 35,345 by trust here, #5,390 by citations
• Natural Language Processing — 50 citations into it
• Representation & Self-Supervised Learning — 31 citations into it

Whom Lin-Jun Yang trusts overall

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

1. Geoffrey E. Hinton
2. Nils Reimers
3. Alexis Conneau
4. Yoshua Bengio
5. Kaiming He
6. Jacob Devlin
7. Diederik P. Kingma
8. Ilya Sutskever
9. Alex Krizhevsky
10. Niklas Muennighoff

Who trusts Lin-Jun Yang overall

1. Hong-Liu Cao

Papers from Lin-Jun Yang's perspective

Ordered by how strongly the researchers Lin-Jun Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
2. Attention is All you Need (Neural Information Processing Systems)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. GloVe: Global Vectors for Word Representation
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Text Embeddings by Weakly-Supervised Contrastive Pre-training (2022) — 1,460 citations
• Improving Text Embeddings with Large Language Models (2023) — 400 citations