64 citations · 64 across the 3 of their papers we have counts for
3 papers
Knowledge Distillation Transfer Sets and their Impact on Downstream NLU Tasks
Charith Peris, Lizhen Tan, Thomas Gueudre +3
Teacher-student knowledge distillation is a popular technique for compressing today's prevailing large language models into manageable sizes that fit low-latency downstream applica…
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems
Jack FitzGerald, Shankar Ananthakrishnan, Konstantine Arkoudas +38
We present results from a large-scale experiment on pretraining encoders with non-embedding parameter counts ranging from 700M to 9.3B, their subsequent distillation into smaller m…
Using multiple ASR hypotheses to boost i18n NLU performance
Charith Peris, Gokmen Oz, Khadige Abboud +3
Current voice assistants typically use the best hypothesis yielded by their Automatic Speech Recognition (ASR) module as input to their Natural Language Understanding (NLU) module,…