5 citations · 6 across the 4 of their papers we have counts for
4 papers
Self-Aware Feedback-Based Self-Learning in Large-Scale Conversational AI
Pragaash Ponnusamy, Clint Solomon Mathialagan, Gustavo Aguilar +2
Self-learning paradigms in large-scale conversational AI agents tend to leverage user feedback in bridging between what they say and what they mean. However, such learning, particu…
A Vocabulary-Free Multilingual Neural Tokenizer for End-to-End Task Learning
Md Mofijul Islam, Gustavo Aguilar, Pragaash Ponnusamy +3
Subword tokenization is a commonly used input pre-processing step in most recent NLP models. However, it limits the models' ability to leverage end-to-end task learning. Its freque…
Personalized Query Rewriting in Conversational AI Agents
Alireza Roshan-Ghias, Clint Solomon Mathialagan, Pragaash Ponnusamy +2
Spoken language understanding (SLU) systems in conversational AI agents often experience errors in the form of misrecognitions by automatic speech recognition (ASR) or semantic gap…
Feedback-Based Self-Learning in Large-Scale Conversational AI Agents
Pragaash Ponnusamy, Alireza Roshan Ghias, Chenlei Guo +1
Today, most large-scale conversational AI agents (e.g. Alexa, Siri, or Google Assistant) are built using manually annotated data to train the different components of the system. Ty…