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Found 7 papers, 2 papers with code
TOAD: Task-Oriented Automatic Dialogs with Diverse Response Styles
In light of recent advances in large language models (LLMs), the expectations for the next generation of virtual assistants include enhanced naturalness and adaptability across diverse usage scenarios.
Prompting for a conversation: How to control a dialog model?
Dialog modelling faces a difficult trade-off.
Plan-then-Generate: Controlled Data-to-Text Generation via Planning
However, the lack of ability of neural models to control the structure of generated output can be limiting in certain real-world applications.
A Generative Model for Joint Natural Language Understanding and Generation
This approach allows us to explore both spaces of natural language and formal representations, and facilitates information sharing through the latent space to eventually benefit NLU and NLG.
Natural Language Understanding
Task-Oriented Dialogue Systems
+1
A Proposition-Based Abstractive Summariser
It is a further development of an existing summariser that has an incremental, proposition-based content selection process but lacks a natural language (NL) generator for the final output.
