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Found 4 papers, 1 papers with code
Training data reduction for multilingual Spoken Language Understanding systems
Fine-tuning self-supervised pre-trained language models such as BERT has significantly improved state-of-the-art performance on natural language processing tasks.
A Survey on Knowledge Editing of Neural Networks
That is expensive, unreliable, and incompatible with the current trend of large self-supervised pre-training, making it necessary to find more efficient and effective methods for adapting neural network models to changing data.
The Massively Multilingual Natural Language Understanding 2022 (MMNLU-22) Workshop and Competition
Despite recent progress in Natural Language Understanding (NLU), the creation of multilingual NLU systems remains a challenge.
MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages
We present the MASSIVE dataset--Multilingual Amazon Slu resource package (SLURP) for Slot-filling, Intent classification, and Virtual assistant Evaluation.
Ranked #1 on
Slot Filling
on MASSIVE
