Hong Chen

Artificial Intelligence · with Li · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 34 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 65 citations into it
• Natural Language Processing — 44 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Information Extraction — 8 citations into it
• Model Architectures — 5 citations into it

Whom Hong Chen trusts overall

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

1. Tao Yu
2. Noam Shazeer
3. Sepp Hochreiter
4. Geoffrey E. Hinton
5. Peter Shaw
6. Yoshua Bengio
7. Diederik P. Kingma
8. Ashish Vaswani
9. J. Urgen Schmidhuber
10. Alex Krizhevsky

Papers from Hong Chen's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Long Short-Term Memory
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
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. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
10. Gradient-based learning applied to document recognition

Their papers

• CodeS: Towards Building Open-source Language Models for Text-to-SQL (2024) — 313 citations
• RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL (2023) — 379 citations