Don Husa

Artificial Intelligence · 2023

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

Subfields

Whom Don Husa trusts

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

  1. Jordan L. Boyd-Graber (in Artificial Intelligence)

Papers from Don Husa's perspective

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

  1. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  2. RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)
  3. SQuAD: 100,000+ Questions for Machine Comprehension of Text
  4. TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
  5. Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
  6. Scaling Laws for Neural Language Models (arXiv.org)
  7. Training language models to follow instructions with human feedback (Neural Information Processing Systems)
  8. Enriching Word Vectors with Subword Information
  9. RACE: Large-scale ReAding Comprehension Dataset From Examinations
  10. SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing

Their papers