We introduce contrastive learning into dialogue generation, where the model explicitly perceives the difference between the well-chosen positive and negative ...

Sep 16, 2020 · To manage the multi-mapping relations prevailed in human conversation, we augment contrastive dialogue learning with group-wise dual sampling.

This work introduces contrastive learning into dialogue generation, where the model explicitly perceives the difference between the well-chosen positive and ...

During contrastive learning, the target dialogue model is trained to give higher conditional probabilities for the positive samples, and lower conditional ...

Oct 13, 2020 · The proposed group-wise contrastive learning framework is suited for training various neural di- alogue generation models. We conduct extensive.

We introduce contrastive learning into persona consistent dialogue generation, building on the idea that humans learn not just from positive feedback.

Contrastive learning is one such technique to learn an embedding space such that similar data sample pairs have close representations.

Data Manipulation: Towards Effective Instance Learning for Neural Dialogue Generation via Learning to Augment and Reweight ... Group-wise contrastive learning for ...

Dialogue generation is the task of "understanding" natural language inputs - within natural language processing in order to produce output.

It uses a timeline of events as an alternative to presenting facts to a group. A demonstration learning strategy is used to share principles or techniques ...