5 papers
Constraint based Knowledge Base Distillation in End-to-End Task Oriented Dialogs
Dinesh Raghu, Atishya Jain, Mausam +1
End-to-End task-oriented dialogue systems generate responses based on dialog history and an accompanying knowledge base (KB). Inferring those KB entities that are most relevant for…
Mask & Focus: Conversation Modelling by Learning Concepts
Gaurav Pandey, Dinesh Raghu, Sachindra Joshi
Sequence to sequence models attempt to capture the correlation between all the words in the input and output sequences. While this is quite useful for machine translation where the…
Unsupervised Learning of Interpretable Dialog Models
Dhiraj Madan, Dinesh Raghu, Gaurav Pandey +1
Recently several deep learning based models have been proposed for end-to-end learning of dialogs. While these models can be trained from data without the need for any additional a…
Multi-level Memory for Task Oriented Dialogs
Revanth Reddy, Danish Contractor, Dinesh Raghu +1
Recent end-to-end task oriented dialog systems use memory architectures to incorporate external knowledge in their dialogs. Current work makes simplifying assumptions about the str…
Disentangling Language and Knowledge in Task-Oriented Dialogs
Dinesh Raghu, Nikhil Gupta, Mausam
The Knowledge Base (KB) used for real-world applications, such as booking a movie or restaurant reservation, keeps changing over time. End-to-end neural networks trained for these…