Goal-Oriented Dialogue Systems
12 papers with code • 0 benchmarks • 4 datasets
Achieving a pre-defined goal through a dialog.
Benchmarks
These leaderboards are used to track progress in Goal-Oriented Dialogue Systems
MultiDoc2Dial
MMD
DSTC7 Task 1
Latest papers with no code
Update Frequently, Update Fast: Retraining Semantic Parsing Systems in a Fraction of Time
To reduce training time, one can fine-tune the previously trained model on each patch, but naive fine-tuning exhibits catastrophic forgetting - degradation of the model performance on the data not represented in the data patch.
End-to-End Neural Pipeline for Goal-Oriented Dialogue Systems using GPT-2
The goal-oriented dialogue system needs to be optimized for tracking the dialogue flow and carrying out an effective conversation under various situations to meet the user goal.
Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems
In recent years, the emerging topics of recommender systems that take advantage of natural language processing techniques have attracted much attention, and one of their applications is the Conversational Recommender System (CRS).
Learning to Classify Intents and Slot Labels Given a Handful of Examples
Prototypical networks achieves significant gains in IC performance on the ATIS and TOP datasets, while both prototypical networks and MAML outperform the baseline with respect to SF on all three datasets.
Attention over Parameters for Dialogue Systems
Dialogue systems require a great deal of different but complementary expertise to assist, inform, and entertain humans.
Planning for Goal-Oriented Dialogue Systems
Generating complex multi-turn goal-oriented dialogue agents is a difficult problem that has seen a considerable focus from many leaders in the tech industry, including IBM, Google, Amazon, and Microsoft.
Data-Efficient Goal-Oriented Conversation with Dialogue Knowledge Transfer Networks
Our main dataset is the Stanford Multi-Domain dialogue corpus.
Few-Shot Dialogue Generation Without Annotated Data: A Transfer Learning Approach
Learning with minimal data is one of the key challenges in the development of practical, production-ready goal-oriented dialogue systems.
DSTC7 Task 1: Noetic End-to-End Response Selection
Goal-oriented dialogue in complex domains is an extremely challenging problem and there are relatively few datasets.
Ordinal and Attribute Aware Response Generation in a Multimodal Dialogue System
Multimodal dialogue systems have opened new frontiers in the traditional goal-oriented dialogue systems.
