Latent Multi-task Architecture Learning
Table 4: Test accuracy scores for different target domains with nw as source domain for named entity recognition (main task) and simplified semantic role labeling with POS tagging as auxiliary task for baselines and Sluice networks. ID: in-domain. OOD: out-of-domain.
['Named entity recognition', 'Named entity recognition System', 'Named entity recognition nw (ID)', 'Named entity recognition bc', 'Named entity recognition bn', 'Named entity recognition mz', 'Named entity recognition pt', 'Named entity recognition tc', 'Named entity recognition wb', 'OOD Avg']
We now evaluate sluice nets on NER with POS tagging as auxiliary task and simplified semantic role labeling with POS tagging as auxiliary task. Sluice networks outperform the comparison models for both tasks on in-domain test data and successfully generalize to out-of-domain test data on average. They yield the best performance on 5 out of 7 domains and 4 out of 7 domains for NER and semantic role labeling.