activity
20182021
most citedFrom Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap

16 citations · 19 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL20213 cited

Alexa Conversations: An Extensible Data-driven Approach for Building Task-oriented Dialogue Systems

Anish Acharya, Suranjit Adhikari, Sanchit Agarwal +28

Traditional goal-oriented dialogue systems rely on various components such as natural language understanding, dialogue state tracking, policy learning and response generation. Trai…

cs.CL2021

Few Shot Dialogue State Tracking using Meta-learning

Saket Dingliwal, Bill Gao, Sanchit Agarwal +3

Dialogue State Tracking (DST) forms a core component of automated chatbot based systems designed for specific goals like hotel, taxi reservation, tourist information, etc. With the…

cs.CL202016 cited

From Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap

Shuyang Gao, Sanchit Agarwal, Tagyoung Chung +2

Dialogue state tracking (DST) is at the heart of task-oriented dialogue systems. However, the scarcity of labeled data is an obstacle to building accurate and robust state tracking…

cs.CL2019

Dialog State Tracking: A Neural Reading Comprehension Approach

Shuyang Gao, Abhishek Sethi, Sanchit Agarwal +2

Dialog state tracking is used to estimate the current belief state of a dialog given all the preceding conversation. Machine reading comprehension, on the other hand, focuses on bu…

cs.CL2018

Parsing Coordination for Spoken Language Understanding

Sanchit Agarwal, Rahul Goel, Tagyoung Chung +3

Typical spoken language understanding systems provide narrow semantic parses using a domain-specific ontology. The parses contain intents and slots that are directly consumed by do…