When is multitask learning effective? Semantic sequence prediction under varying data conditions

Understand

Multitask learning has been applied successfully to a range of tasks, mostly morphosyntactic.

• However, little is known on when MTL works and whether there are data characteristics that help to determine its success.
• In this paper we evaluate a range of semantic sequence labeling tasks in a MTL setup.
• We examine different auxiliary tasks, amongst which a novel setup, and correlate their impact to data-dependent conditions.