Yijia Shao

Artificial Intelligence · 2022–2024

A researcher in the Science corpus: 4 papers; trusts 121 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 166 citations into it
• Computer Vision and Pattern Recognition — 71 citations into it
• Natural Language Processing — 53 citations into it
• Large Language Models — 47 citations into it
• Meta & Continual Learning — 38 citations into it
• Prompting & Reasoning — 24 citations into it
• Model Architectures — 11 citations into it
• Reinforcement Learning — 11 citations into it

Whom Yijia Shao trusts overall

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

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

Who trusts Yijia Shao overall

1. Zixuan Ke

Papers from Yijia Shao's perspective

Ordered by how strongly the researchers Yijia Shao 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. Learning Multiple Layers of Features from Tiny Images
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking (2024) — 317 citations
• Continual Pre-training of Language Models (2023) — 242 citations
• CMG: A Class-Mixed Generation Approach to Out-of-Distribution Detection (2022) — 15 citations
• Continual Training of Language Models for Few-Shot Learning (2022) — 45 citations