Information-Theoretic Probing for Linguistic Structure

Understand

The success of neural networks on a diverse set of NLP tasks has led researchers to question how much these networks actually ``know'' about natural language.

• Probes are a natural way of assessing this.
• When probing, a researcher chooses a linguistic task and trains a supervised model to predict annotations in that linguistic task from the network's learned representations.
• If the probe does well, the researcher may conclude that the representations encode knowledge related to the task.