Deep Cascade Multi-task Learning for Slot Filling in Online
Deep Cascade Multi-task Learning for Slot Filling in Online
The goal of slot filling is to identify slots corresponding to different parameters of the user's query With the help of slot-filling models,
We adopt a fine-tuning approach where a pre-trained LLM is fine-tuned into a slot-filling model using task specific data The fine-tuning data is prepared SLOT FILL FACTOR Slot fill factor is the ratio of the cross-sectional area occupied by copper wire inside the stator slot to the total amount of available
7s wild slot machine The goal of Slot Filling is to identify from a running dialog different slots, which correspond to different parameters of the user's query A slot-filling task is most simple task of dialogue system Typical domain of this task are telephone shopping, on-line banking, on-line trade, etc
![Deep Cascade Multi-task Learning for Slot Filling in Online](10011.png)