HyperEmbed: Tradeoffs Between Resources and Performance in NLP Tasks with Hyperdimensional Computing enabled Embedding of n-gram Statistics
Table 12: F1 score comparison of various platforms on three smaller datasets with methods mentioned in the paper. Some results are taken from Shridhar et al. (2019)
['Platform', 'Chatbot', 'AskUbuntu', 'WebApp', 'Average']
There were some data augmentation techniques, which were used in the paper, most prominently a QWERTY-based word augmentation accounting for the spelling mistakes. This technique was not used in this work, which resulted in a slight difference in the obtained F1 scores.