activity
20202022
most citedAutomatic Discovery of Novel Intents & Domains from Text Utterances

13 citations · 19 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2022

Instilling Type Knowledge in Language Models via Multi-Task QA

Shuyang Li, Mukund Sridhar, Chandana Satya Prakash +3

Understanding human language often necessitates understanding entities and their place in a taxonomy of knowledge -- their types. Previous methods to learn entity types rely on tra…

cs.CL2021

Towards Realistic Single-Task Continuous Learning Research for NER

Justin Payan, Yuval Merhav, He Xie +4

There is an increasing interest in continuous learning (CL), as data privacy is becoming a priority for real-world machine learning applications. Meanwhile, there is still a lack o…

cs.CL20215 cited

Zero-shot Generalization in Dialog State Tracking through Generative Question Answering

Shuyang Li, Jin Cao, Mukund Sridhar +4

Dialog State Tracking (DST), an integral part of modern dialog systems, aims to track user preferences and constraints (slots) in task-oriented dialogs. In real-world settings with…

cs.CL202013 cited

Automatic Discovery of Novel Intents & Domains from Text Utterances

Nikhita Vedula, Rahul Gupta, Aman Alok +1

One of the primary tasks in Natural Language Understanding (NLU) is to recognize the intents as well as domains of users' spoken and written language utterances. Most existing rese…

cs.LG20201 cited

Towards classification parity across cohorts

Aarsh Patel, Rahul Gupta, Mukund Harakere +3

Recently, there has been a lot of interest in ensuring algorithmic fairness in machine learning where the central question is how to prevent sensitive information (e.g. knowledge a…