7 citations · 11 across the 5 of their papers we have counts for
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cs.CL2022
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…
cs.CL2020
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,…
cs.CL2020
Generative Adversarial Networks for Annotated Data Augmentation in Data Sparse NLU
Olga Golovneva, Charith Peris
Data sparsity is one of the key challenges associated with model development in Natural Language Understanding (NLU) for conversational agents. The challenge is made more complex b…