Improving Robustness of Task Oriented Dialog Systems

no code implementations • 12 Nov 2019 • Arash Einolghozati, Sonal Gupta, Mrinal Mohit, Rushin Shah

However, evaluating a model's robustness to these changes is harder for language since words are discrete and an automated change (e. g. adding `noise') to a query sometimes changes the meaning and thus labels of a query.

Adversarial Attack Data Augmentation +4

Improving Semantic Parsing for Task Oriented Dialog

no code implementations • 15 Feb 2019 • Arash Einolghozati, Panupong Pasupat, Sonal Gupta, Rushin Shah, Mrinal Mohit, Mike Lewis, Luke Zettlemoyer

Semantic parsing using hierarchical representations has recently been proposed for task oriented dialog with promising results [Gupta et al 2018].

Language Modelling Re-Ranking +1

PyText: A Seamless Path from NLP research to production

2 code implementations • 12 Dec 2018 • Ahmed Aly, Kushal Lakhotia, Shicong Zhao, Mrinal Mohit, Barlas Oguz, Abhinav Arora, Sonal Gupta, Christopher Dewan, Stef Nelson-Lindall, Rushin Shah

We introduce PyText - a deep learning based NLP modeling framework built on PyTorch.

Semantic Parsing for Task Oriented Dialog using Hierarchical Representations

no code implementations • EMNLP 2018 • Sonal Gupta, Rushin Shah, Mrinal Mohit, Anuj Kumar, Mike Lewis

Task oriented dialog systems typically first parse user utterances to semantic frames comprised of intents and slots.

Constituency Parsing Semantic Parsing +2