Breakthrough Technique: Meta-learning for Compositionality
Original :
https://www.nature.com/articles/s41586-023-06668-3
Vulgarization :
https://scitechdaily.com/the-future-of-machine-learning-a-new-breakthrough-technique/
How MLC Works
In exploring the possibility of bolstering compositional learning in neural networks, the researchers created MLC, a novel learning procedure in which a neural network is continuously updated to improve its skills over a series of episodes. In an episode, MLC receives a new word and is asked to use it compositionally—for instance, to take the word “jump” and then create new word combinations, such as “jump twice” or “jump around right twice.” MLC then receives a new episode that features a different word, and so on, each time improving the network’s compositional skills.
To be clear, the papers at conferences undergo a peer review process as well. There are journal publications in CS, but a lot of publishing is done through conferences. Arxiv, while a great resource, has little to do with the conferences and it is worth noting that the papers on arxiv do not go through a peer review process (but are often published at conferences where the paper has gone under peer review — some papers on arxiv may be preprint versions from before the peer review process).