Di Jin

Artificial Intelligence · with Liu · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 107 citations into it
• Natural Language Processing — 69 citations into it
• Safety, Robustness & Interpretability — 32 citations into it
• Evaluation & Benchmarks — 10 citations into it

Whom Di Jin trusts overall

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

1. Emily Dinan
2. Diederik P. Kingma
3. Jason Aaron Edward Weston
4. Geoffrey E. Hinton
5. Jacob Devlin
6. Yoshua Bengio
7. Ilya Sutskever
8. Alex Krizhevsky
9. Jing Xu
10. Jimmy Ba

Papers from Di Jin's perspective

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

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

Their papers

• Using In-Context Learning to Improve Dialogue Safety (2023) — 60 citations
• DialGuide: Aligning Dialogue Model Behavior with Developer Guidelines (2022) — 6 citations