Multitask learning for semantic sequence prediction under varying data conditions

  title={Multitask learning for semantic sequence prediction under varying data conditions},
  author={H{\'e}ctor Mart{\'i}nez Alonso and Barbara Plank},
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 the success of MTL. In this paper we evaluate a range of semantic sequence labeling tasks in a MTL setup. We examine different auxiliary task configurations, amongst which a novel setup, and correlate their impact to data-dependent conditions. Our results show that MTL is not always effective… CONTINUE READING
Recent Discussions
This paper has been referenced on Twitter 20 times over the past 90 days. VIEW TWEETS

From This Paper

Figures, tables, results, connections, and topics extracted from this paper.
9 Extracted Citations
29 Extracted References
Similar Papers

Similar Papers

Loading similar papers…