ML and NLP Research Highlights of 2021

Credit for the title image: Liu et al. (2021)

2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). In this post, I will cover the papers and research areas that I found most inspiring. I tried to cover the papers that I was aware of but likely missed many relevant ones. Feel free to highlight them as well as ones that you found inspiring in the comments. I discuss the following highlights:

  1. Universal Models
  2. Massive Multi-task Learning
  3. Beyond the Transformer
  4. Prompting
  5. Efficient Methods
  6. Benchmarking
  7. Conditional Image Generation
  8. ML for Science
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