Taylor Sorensen

Artificial Intelligence · 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 Taylor Sorensen trusts

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

  1. Chin-Yew Lin (in Natural Language Processing)
  2. Diederik P. Kingma (in Artificial Intelligence)
  3. Yoshua Bengio (in Artificial Intelligence)

Papers from Taylor Sorensen's perspective

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

  1. Language Models are Unsupervised Multitask Learners
  2. Microsoft COCO: Common Objects in Context
  3. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Long Short-Term Memory
  8. Building a Large Annotated Corpus of English: The Penn Treebank
  9. The Curious Case of Neural Text Degeneration
  10. GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Their papers