Nan Yang

Artificial Intelligence · with Wei · 2023–2024

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 65 citations into it; #34,945 of 35,345 by trust here, #13,760 by citations
• Representation & Self-Supervised Learning — 17 citations into it; #3,045 of 3,145 by trust here, #1,811 by citations

Whom Nan Yang trusts overall

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

1. Niklas Muennighoff
2. Nils Reimers
3. Geoffrey E. Hinton
4. Tianyu Gao
5. Liang Wang
6. Yoshua Bengio
7. Jacob Devlin
8. Diederik P. Kingma
9. Tomas Mikolov
10. Ilya Sutskever

Who trusts Nan Yang overall

1. Hong-Liu Cao

Papers from Nan Yang's perspective

Ordered by how strongly the researchers Nan 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. Long Short-Term Memory
5. ImageNet classification with deep convolutional neural networks
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. GloVe: Global Vectors for Word Representation
8. Language Models are Few-Shot Learners (Neural Information Processing Systems)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• LongEmbed: Extending Embedding Models for Long Context Retrieval (2024)
• Generative Representational Instruction Tuning (2024)
• Improving Text Embeddings with Large Language Models (2023) — 400 citations