Yutong Lu
Computer Vision and Pattern Recognition · 2 papers · 2021–2022
A researcher in the Science corpus: 2 papers; trusts 270 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 72 citations into it
- Artificial Intelligence — 55 citations into it
- Multimodal Learning — 37 citations into it
- Natural Language Processing — 20 citations into it
- Generative Models — 19 citations into it
- Evaluation & Benchmarks — 11 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
- Large Language Models — 6 citations into it
Whom Yutong Lu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Yoshua Bengio
- Alex Krizhevsky
- Ross B. Girshick
- Ilya Sutskever
- Jimmy Ba
- Yann LeCun
- Karen Simonyan
Papers from Yutong Lu's perspective
Ordered by how strongly the researchers Yutong Lu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking (2022) — 833 citations
- Unifying Multimodal Transformer for Bi-directional Image and Text Generation (2021) — 67 citations