Hybrid Generative-Retrieval Transformers for Dialogue Domain Adaptation

Understand

Domain adaptation has recently become a key problem in dialogue systems research.

• Deep learning, while being the preferred technique for modeling such systems, works best given massive training data.
• However, in the real-world scenario, such resources aren't available for every new domain, so the ability to train with a few dialogue examples can be considered essential.
• Pre-training on large data sources and adapting to the target data has become the standard method for few-shot problems within the deep learning framework.