Binhang Yuan

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 120 citations into it
• Efficiency & Compression — 49 citations into it
• Large Language Models — 40 citations into it

Whom Binhang Yuan trusts overall

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

1. Geoffrey E. Hinton
2. Praneeth Vepakomma
3. Jakub Konecný
4. Alex Krizhevsky
5. Kaiming He
6. Yoshua Bengio
7. Jie Xu
8. Awni Y. Hannun
9. Yann LeCun
10. Diederik P. Kingma

Who trusts Binhang Yuan overall

1. Dinh C. Nguyen
2. Ming Ding

Papers from Binhang Yuan's perspective

Ordered by how strongly the researchers Binhang Yuan 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Learning Multiple Layers of Features from Tiny Images
10. Distilling the Knowledge in a Neural Network (arXiv.org)

Their papers

• Holistic Evaluation of Language Models (2023) — 1,863 citations
• High-throughput Generative Inference of Large Language Models with a Single GPU (2023) — 797 citations
• Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time (2023) — 356 citations
• A Federated Learning Framework for Healthcare IoT devices (2020) — 85 citations