no code implementations • 12 Feb 2023 • Xavier Amatriain, Ananth Sankar, Jie Bing, Praveen Kumar Bodigutla, Timothy J. Hazen, Michaeel Kazi
The goal of this paper is to offer a somewhat comprehensive but simple catalog and classification of the most popular Transformer models.
no code implementations • 10 Aug 2021 • Praveen Kumar Bodigutla
To recommend high quality related search queries, we train a Deep Reinforcement Learning model to predict the query a user would enter next.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Praveen Kumar Bodigutla, Aditya Tiwari, Josep Valls Vargas, Lazaros Polymenakos, Spyros Matsoukas
Dialogue level quality estimation is vital for optimizing data driven dialogue management.
no code implementations • 18 Nov 2019 • Praveen Kumar Bodigutla, Lazaros Polymenakos, Spyros Matsoukas
To address these gaps, we created a new Response Quality annotation scheme, introduced five new domain-independent feature sets and experimented with six machine learning models to estimate User Satisfaction at both turn and dialogue level.
no code implementations • 19 Aug 2019 • Praveen Kumar Bodigutla, Longshaokan Wang, Kate Ridgeway, Joshua Levy, Swanand Joshi, Alborz Geramifard, Spyros Matsoukas
An automated metric to evaluate dialogue quality is vital for optimizing data driven dialogue management.