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20182020
most citedImproving Semantic Parsing for Task Oriented Dialog

25 citations · 47 across the 3 of their papers we have counts for

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cs.CL2020

Sound Natural: Content Rephrasing in Dialog Systems

Arash Einolghozati, Anchit Gupta, Keith Diedrick +1

We introduce a new task of rephrasing for a more natural virtual assistant. Currently, virtual assistants work in the paradigm of intent slot tagging and the slot values are direct…

cs.CL2020

Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing

Xilun Chen, Asish Ghoshal, Yashar Mehdad +2

Task-oriented semantic parsing is a critical component of virtual assistants, which is responsible for understanding the user's intents (set reminder, play music, etc.). Recent adv…

cs.CL2020

Conversational Semantic Parsing

Armen Aghajanyan, Jean Maillard, Akshat Shrivastava +8

The structured representation for semantic parsing in task-oriented assistant systems is geared towards simple understanding of one-turn queries. Due to the limitations of the repr…

cs.CL20192 cited

Likelihood Ratios and Generative Classifiers for Unsupervised Out-of-Domain Detection In Task Oriented Dialog

Varun Gangal, Abhinav Arora, Arash Einolghozati +1

The task of identifying out-of-domain (OOD) input examples directly at test-time has seen renewed interest recently due to increased real world deployment of models. In this work,…

cs.CL201925 cited

Improving Semantic Parsing for Task Oriented Dialog

Arash Einolghozati, Panupong Pasupat, Sonal Gupta +4

Semantic parsing using hierarchical representations has recently been proposed for task oriented dialog with promising results [Gupta et al 2018]. In this paper, we present three d…

cs.CL2018

Semantic Parsing for Task Oriented Dialog using Hierarchical Representations

Sonal Gupta, Rushin Shah, Mrinal Mohit +2

Task oriented dialog systems typically first parse user utterances to semantic frames comprised of intents and slots. Previous work on task oriented intent and slot-filling work ha…