2022: A Year in Review (ML Papers Edition)

Let’s take a look at some of the top trending ML papers of 2022:

1) A ConvNet for the 2020s (Liu et al) — Vision Transformers took off this year but this work proposes ConvNeXt to reexamine the design spaces and test the limits of a pure ConvNet on several vision tasks. The ConvNets vs. Transformers debate continues.

2) Language Models as Zero-Shot Planners (Huang et al) — studies the possibility of grounding high-level tasks to actionable steps for embodied agents. Pre-trained LLMs are used to extract knowledge to perform common-sense grounding by planning




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