Yukun Li
Artificial Intelligence · with Tian · 2018–2020
A researcher in the Science corpus: 5 papers; trusts 44 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 105 citations into it; #26,690 of 35,345 by trust here, #5,834 by citations
- Natural Language Processing — 97 citations into it; #4,389 of 5,688 by trust here, #1,407 by citations
- Large Language Models — 36 citations into it; #533 of 799 by trust here, #415 by citations
- Evaluation & Benchmarks — 32 citations into it
- Information Systems — 5 citations into it
- Molecular Biology — 5 citations into it
Whom Yukun Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Alec Radford
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Min-Ling Zhang
- Jimmy Ba
- Yann LeCun
- Ashish Vaswani
Who trusts Yukun Li overall
Papers from Yukun Li's perspective
Ordered by how strongly the researchers Yukun Li 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- 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)
Their papers
- ERNIE: Enhanced Representation through Knowledge Integration (2019) — 1,025 citations
- ERNIE 2.0: A Continual Pre-training Framework for Language Understanding (2019) — 902 citations
- ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation (2020) — 135 citations
- ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding (2020) — 43 citations
- Binary relevance for multi-label learning: an overview (2018) — 422 citations