Fanyi Pu

Computer Vision and Pattern Recognition · 2023–2024

A researcher in the Science corpus: 3 papers; trusts 163 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 99 citations into it
• Artificial Intelligence — 92 citations into it
• Multimodal Learning — 53 citations into it

Whom Fanyi Pu trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Yoshua Bengio
5. Diederik P. Kingma
6. Ross B. Girshick
7. Ilya Sutskever
8. Yann LeCun
9. Tsung-Yi Lin
10. Karen Simonyan

Papers from Fanyi Pu's perspective

Ordered by how strongly the researchers Fanyi Pu 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. ImageNet classification with deep convolutional neural networks
3. ImageNet: A large-scale hierarchical image database
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Microsoft COCO: Common Objects in Context
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• MIMIC-IT: Multi-Modal In-Context Instruction Tuning (2023) — 310 citations
• LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models (2024) — 331 citations
• OtterHD: A High-Resolution Multi-modality Model (2023) — 87 citations