Estimating the influence of auxiliary tasks for multi-task learning of sequence tagging tasks (2020.acl-main)
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| Challenge: | Multitask learning and transfer learning are techniques to overcome data scarcity . finding suitable auxiliary datasets for multitask learning is a trial-and-error approach . |
| Approach: | They propose to automatically assess the similarity of sequence tagging datasets to identify beneficial auxiliary data for MTL or TL setups. |
| Outcome: | The proposed methods can compute similarity between two sequence tagging datasets . they show that the same measures correlate with the change in test score of the auxiliary dataset . |
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