W. Liang

Artificial Intelligence · Annual Meeting of the Association for Computational Linguistics · 2024–2026

A researcher in the Science corpus: 10 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom W. Liang trusts

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

  1. Noam Shazeer (in Artificial Intelligence)

Papers from W. Liang's perspective

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

  1. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  2. Language Models are Unsupervised Multitask Learners
  3. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
  4. Neural Machine Translation of Rare Words with Subword Units
  5. Scaling Laws for Neural Language Models (arXiv.org)
  6. Training language models to follow instructions with human feedback (Neural Information Processing Systems)
  7. Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
  8. The Pile: An 800GB Dataset of Diverse Text for Language Modeling
  9. TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
  10. Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity (Journal of machine learning research)

Their papers