Joshua Lane

Artificial Intelligence · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Joshua Lane trusts

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

  1. Jason Aaron Edward Weston (in Artificial Intelligence)
  2. Kurt Shuster (in Natural Language Processing)
  3. Y-Lan Boureau (in Artificial Intelligence)
  4. Emily Dinan (in Artificial Intelligence)
  5. Diederik P. Kingma (in Artificial Intelligence)
  6. Yoshua Bengio (in Artificial Intelligence)

Papers from Joshua Lane's perspective

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

  1. Attention is All you Need (Neural Information Processing Systems)
  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. RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)
  5. SQuAD: 100,000+ Questions for Machine Comprehension of Text
  6. The Curious Case of Neural Text Degeneration
  7. TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
  8. Improved Techniques for Training GANs
  9. Training language models to follow instructions with human feedback (Neural Information Processing Systems)
  10. Learning Transferable Visual Models From Natural Language Supervision (International Conference on Machine Learning)

Their papers