24 citations · 66 across the 16 of their papers we have counts for
6 papers · 1 filter
Learning Slice-Aware Representations with Mixture of Attentions
Cheng Wang, Sungjin Lee, Sunghyun Park +3
Real-world machine learning systems are achieving remarkable performance in terms of coarse-grained metrics like overall accuracy and F-1 score. However, model improvement and deve…
Handling Long-Tail Queries with Slice-Aware Conversational Systems
Cheng Wang, Sun Kim, Taiwoo Park +5
We have been witnessing the usefulness of conversational AI systems such as Siri and Alexa, directly impacting our daily lives. These systems normally rely on machine learning mode…
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…
Locale-agnostic Universal Domain Classification Model in Spoken Language Understanding
Jihwan Lee, Ruhi Sarikaya, Young-Bum Kim
In this paper, we introduce an approach for leveraging available data across multiple locales sharing the same language to 1) improve domain classification model accuracy in Spoken…
Continuous Learning for Large-scale Personalized Domain Classification
Han Li, Jihwan Lee, Sidharth Mudgal +2
Domain classification is the task of mapping spoken language utterances to one of the natural language understanding domains in intelligent personal digital assistants (IPDAs). Thi…
Differentiable Greedy Networks
Thomas Powers, Rasool Fakoor, Siamak Shakeri +4
Optimal selection of a subset of items from a given set is a hard problem that requires combinatorial optimization. In this paper, we propose a subset selection algorithm that is t…