Prior Knowledge Driven Label Embedding for Slot Filling in Natural Language Understanding
TABLE IX: Slot F1 scores on SNIPS test set in the setting of domain adaptation with only 50 instances of each target intent for fine-tuning.
['[BOLD] Method', 'Average Slot F1']
We also report results on the SNIPS public dataset where one intent are kept as the target domain and the rest intents serve as the source domain. Only 50 train instances of the target domain can be utilized for fine-tuning, which are chosen in random. All 7 intents play a role of the target domain one by one, and the slot F1 scores are averaged over seven target domains. Especially, the “slot exemplar (BiLMs)” method achieves the best slot F1 score.