Jue Wang

Artificial Intelligence · with Zhang · 2022–2024

A researcher in the Science corpus: 4 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 131 citations into it
• Computer Vision and Pattern Recognition — 65 citations into it
• Model Architectures — 21 citations into it
• Representation & Self-Supervised Learning — 9 citations into it

Whom Jue Wang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Yann LeCun
6. Diederik P. Kingma
7. Ilya Sutskever
8. X. Zhang
9. Ross B. Girshick
10. Oriol Vinyals

Papers from Jue Wang's perspective

Ordered by how strongly the researchers Jue Wang 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Holistic Evaluation of Language Models (2023) — 1,863 citations
• Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time (2023) — 356 citations
• Mixture-of-Agents Enhances Large Language Model Capabilities (2024) — 450 citations
• Continual Federated Learning Based on Knowledge Distillation (2022) — 132 citations