A RuBERT model fine-tuned on 100 Russian sentences plus sliding-window augmentation reports F1 0.8642 for part-of-speech tagging, but without external validation or baseline comparisons.
Neural Machine Translation with Byte-Level Subwords // 2019
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2024 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
POS-tagging to highlight the skeletal structure of sentences
A RuBERT model fine-tuned on 100 Russian sentences plus sliding-window augmentation reports F1 0.8642 for part-of-speech tagging, but without external validation or baseline comparisons.