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Leveraging User Paraphrasing Behavior In Dialog Systems To Automatically Collect Annotations For Long-Tail Utterances
In large-scale commercial dialog systems, users express the same request in a wide variety of alternative ways with a long tail of less frequent alternatives.
Feedback Attribution for Counterfactual Bandit Learning in Multi-Domain Spoken Language Understanding
With counterfactual bandit learning, models can be trained based on positive and negative feedback received for historical predictions, with no labeled data needed.
Multilingual Paraphrase Generation For Bootstrapping New Features in Task-Oriented Dialog Systems
As a solution, we propose a multilingual paraphrase generation model that can be used to generate novel utterances for a target feature and target language.
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