Papers by Ruotong Geng

1 papers
Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation (2023.acl-long)

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Challenge: Existing controllable dialogue generation models focus on single attribute and lack generalization capability to out-of-distribution multiple attribute combinations.
Approach: They propose a compositional generalization model that learns from seen attributes and generalizes to unseen combinations.
Outcome: The proposed model can learn from seen attribute values and generalize to unseen combinations.

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