Xinyi Wu

Artificial Intelligence · with Wang · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 75 citations into it; #26,607 of 35,345 by trust here, #22,463 by citations
• Natural Language Processing — 73 citations into it; #4,374 of 5,688 by trust here, #4,250 by citations
• Large Language Models — 10 citations into it

Whom Xinyi Wu trusts overall

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

1. Ann A. Copestake
2. Alec Radford
3. R. Thomas McCoy
4. Jacob Devlin

Who trusts Xinyi Wu overall

1. Sarah Wiegreffe
2. Ana Marasovic

Papers from Xinyi Wu's perspective

Ordered by how strongly the researchers Xinyi Wu 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. Language Models are Unsupervised Multitask Learners
3. Attention is All you Need (Neural Information Processing Systems)
4. Long Short-Term Memory
5. ImageNet classification with deep convolutional neural networks
6. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
7. Improving Language Understanding by Generative Pre-Training
8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)

Their papers

• NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2021) — 104 citations
• Linguistically-Informed Transformations (LIT): A Method for Automatically Generating Contrast Sets (2020) — 44 citations