25 citations · 102 across the 10 of their papers we have counts for
10 papers
PRESTO: A Multilingual Dataset for Parsing Realistic Task-Oriented Dialogs
Rahul Goel, Waleed Ammar, Aditya Gupta +13
Research interest in task-oriented dialogs has increased as systems such as Google Assistant, Alexa and Siri have become ubiquitous in everyday life. However, the impact of academi…
Metric-Free Exploration for Topological Mapping by Task and Motion Imitation in Feature Space
Yuhang He, Irving Fang, Yiming Li +2
We propose DeepExplorer, a simple and lightweight metric-free exploration method for topological mapping of unknown environments. It performs task and motion planning (TAMP) entire…
DAMP: Doubly Aligned Multilingual Parser for Task-Oriented Dialogue
William Held, Christopher Hidey, Fei Liu +4
Modern virtual assistants use internal semantic parsing engines to convert user utterances to actionable commands. However, prior work has demonstrated that semantic parsing is a d…
Improving Top-K Decoding for Non-Autoregressive Semantic Parsing via Intent Conditioning
Geunseob Oh, Rahul Goel, Chris Hidey +4
Semantic parsing (SP) is a core component of modern virtual assistants like Google Assistant and Amazon Alexa. While sequence-to-sequence-based auto-regressive (AR) approaches are…
Update Frequently, Update Fast: Retraining Semantic Parsing Systems in a Fraction of Time
Vladislav Lialin, Rahul Goel, Andrey Simanovsky +2
Currently used semantic parsing systems deployed in voice assistants can require weeks to train. Datasets for these models often receive small and frequent updates, data patches. E…
Improving Robustness of Task Oriented Dialog Systems
Arash Einolghozati, Sonal Gupta, Mrinal Mohit +1
Task oriented language understanding in dialog systems is often modeled using intents (task of a query) and slots (parameters for that task). Intent detection and slot tagging are,…
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…
PyText: A Seamless Path from NLP research to production
Ahmed Aly, Kushal Lakhotia, Shicong Zhao +7
We introduce PyText - a deep learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of se…
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…
Cross-Lingual Transfer Learning for Multilingual Task Oriented Dialog
Sebastian Schuster, Sonal Gupta, Rushin Shah +1
One of the first steps in the utterance interpretation pipeline of many task-oriented conversational AI systems is to identify user intents and the corresponding slots. Since data…