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cs.CL2021
DG2: Data Augmentation Through Document Grounded Dialogue Generation
Qingyang Wu, Song Feng, Derek Chen +3
Collecting data for training dialog systems can be extremely expensive due to the involvement of human participants and need for extensive annotation. Especially in document-ground…
cs.CL2021
Clean or Annotate: How to Spend a Limited Data Collection Budget
Derek Chen, Zhou Yu, Samuel R. Bowman
Crowdsourcing platforms are often used to collect datasets for training machine learning models, despite higher levels of inaccurate labeling compared to expert labeling. There are…
cs.CL2021
GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation
Derek Chen, Zhou Yu
Practical dialogue systems require robust methods of detecting out-of-scope (OOS) utterances to avoid conversational breakdowns and related failure modes. Directly training a model…