Bailin Wang

Artificial Intelligence · with Kim · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 75 citations into it
• Model Architectures — 52 citations into it
• Computer Vision and Pattern Recognition — 40 citations into it
• Natural Language Processing — 15 citations into it
• Efficiency & Compression — 12 citations into it
• Hardware and Architecture — 10 citations into it
• Electrical and Electronic Engineering — 6 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Bailin Wang trusts overall

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

1. Geoffrey E. Hinton
2. Tri Dao
3. Yoshua Bengio
4. Noam Shazeer
5. J. Urgen Schmidhuber
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Sepp Hochreiter
9. Ilya Sutskever
10. Alex Graves

Papers from Bailin Wang's perspective

Ordered by how strongly the researchers Bailin Wang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Gated Linear Attention Transformers with Hardware-Efficient Training (2023) — 480 citations
• Parallelizing Linear Transformers with the Delta Rule over Sequence Length (2024) — 322 citations