Liying Cheng

Artificial Intelligence · with Bing · 2021–2023

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Liying Cheng trusts

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

  1. Diederik P. Kingma (in Artificial Intelligence)
  2. Jimmy Ba (in Artificial Intelligence)
  3. Sebastian Ruder (in Artificial Intelligence)

Papers from Liying Cheng's perspective

Ordered by how strongly the researchers Liying Cheng 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. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  3. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. ImageNet classification with deep convolutional neural networks
  7. Long Short-Term Memory
  8. RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)
  9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  10. Neural Machine Translation of Rare Words with Subword Units

Their papers