Qiuyuan Huang

Computer Vision and Pattern Recognition · 2017–2023

A researcher in the Science corpus: 10 papers; trusts 606 researchers and is trusted by 102 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 199 citations into it; #3,305 of 21,575 by trust here, #1,964 by citations
• Artificial Intelligence — 188 citations into it; #34,729 of 35,345 by trust here, #6,193 by citations
• Natural Language Processing — 103 citations into it
• Multimodal Learning — 86 citations into it; #365 of 1,211 by trust here, #180 by citations
• Generative Models — 41 citations into it; #714 of 1,956 by trust here, #312 by citations
• Evaluation & Benchmarks — 30 citations into it
• Model Architectures — 28 citations into it
• Reinforcement Learning — 24 citations into it; #2,212 of 2,242 by trust here, #778 by citations

Whom Qiuyuan Huang trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Diederik P. Kingma
4. Yoshua Bengio
5. Alex Krizhevsky
6. Ilya Sutskever
7. Yann LeCun
8. Ross B. Girshick
9. J. Urgen Schmidhuber
10. Alex Graves

Who trusts Qiuyuan Huang overall

1. Tianfu Wu
2. Jiadong Liang
3. Jaemin Cho
4. Yufan Zhou
5. Peter Anderson
6. Tobias Hinz
7. Vihan Jain
8. Jing Yu Koh
9. Hongchen Tan
10. Ming Tao

Papers from Qiuyuan Huang's perspective

Ordered by how strongly the researchers Qiuyuan Huang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks (2017) — 1,976 citations
• Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation (2018) — 642 citations
• Object-Driven Text-To-Image Synthesis via Adversarial Training (2019) — 324 citations
• KAT: A Knowledge Augmented Transformer for Vision-and-Language (2021) — 220 citations
• Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback (2023) — 530 citations
• NICE: Neural Image Commenting with Empathy (2021) — 9 citations
• KB-VLP: Knowledge Based Vision and Language Pretraining (2021)
• Learning Inference Rules with Neural TP-Reasoner (2020)
• Natural- to formal-language generation using Tensor Product Representations (2019) — 3 citations
• Mapping natural-language problems to formal-language solutions using structured neural representations (2019) — 28 citations