Ling Chen

Artificial Intelligence · with Fang · 2023

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Safety, Robustness & Interpretability — 15 citations into it
• Large Language Models — 6 citations into it

Whom Ling Chen trusts overall

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

1. Alec Radford
2. Diederik P. Kingma

Papers from Ling Chen's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
3. Language Models are Unsupervised Multitask Learners
4. Improving Language Understanding by Generative Pre-Training
5. Language Models are Few-Shot Learners (Neural Information Processing Systems)
6. Attention is All you Need (Neural Information Processing Systems)
7. Bleu: a Method for Automatic Evaluation of Machine Translation
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. ImageNet classification with deep convolutional neural networks
10. Long Short-Term Memory

Their papers

• CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models (2023) — 36 citations