Task-oriented semantic parsing models have achieved strong results in re...
Improving the quality of Natural Language Understanding (NLU) models, an...
Data efficiency, despite being an attractive characteristic, is often
ch...
When tuning the architecture and hyperparameters of large machine learni...
Modern task-oriented semantic parsing approaches typically use seq2seq
t...
An effective recipe for building seq2seq, non-autoregressive, task-orien...
Task-oriented semantic parsing models typically have high resource
requi...
Semantic parsing using sequence-to-sequence models allows parsing of dee...
The increasing computational and memory complexities of deep neural netw...
The Lottery Ticket Hypothesis suggests large, over-parameterized neural
...
Deformable shape modeling approaches that describe objects in terms of t...
This paper presents an evolutionary metaheuristic called Multiple Search...
We introduce PyText - a deep learning based NLP modeling framework built...
Asset monitoring in construction sites is an intricate, manually intensi...
Derivative-based optimization techniques such as Stochastic Gradient Des...