Jing Sha

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it
• Natural Language Processing — 14 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Computational Theory and Mathematics — 6 citations into it

Whom Jing Sha trusts overall

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

1. Yoon Kim

Papers from Jing Sha's perspective

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

1. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
2. Attention is All you Need (Neural Information Processing Systems)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Decoupled Weight Decay Regularization
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Long Short-Term Memory
7. ImageNet classification with deep convolutional neural networks
8. Gradient-based learning applied to document recognition
9. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
10. Convolutional Neural Networks for Sentence Classification

Their papers

• Continual Pre-training of Language Models for Math Problem Understanding with Syntax-Aware Memory Network (2022) — 35 citations