Papers with Part-of-speech tagging
BERTweet: A pre-trained language model for English Tweets (2020.emnlp-demos)
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| Challenge: | Experiments show that BERTweet outperforms strong baselines RoBERTa-base and XLM-R-base on three Tweet NLP tasks: Part-of-speech tagging, Named-entity recognition and text classification. |
| Approach: | They propose to train a pre-trained language model for English Tweets using the RoBERTa pre training procedure and use it to train the model. |
| Outcome: | Experiments show that the model outperforms baseline models on three Tweet NLP tasks: Part-of-speech tagging, Named-entity recognition and text classification. |
ViDeBERTa: A powerful pre-trained language model for Vietnamese (2023.findings-eacl)
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| Challenge: | Existing models for Vietnamese that perform well on downstream tasks, such as Question answering, are based on Transformer. |
| Approach: | They propose a pre-trained monolingual Vietnamese model with three versions . they fine-tune and evaluate the model on three important natural language downstream tasks, Part-of-speech tagging, Named-entity recognition, and Question answering. |
| Outcome: | The proposed model outperforms the existing model on three important natural language downstream tasks, Part-of-speech tagging, Named-entity recognition, and Question answering. |
PhoBERT: Pre-trained language models for Vietnamese (2020.findings-emnlp)
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| Challenge: | Experimental results show that PhoBERT outperforms the recent best pre-trained multilingual model XLM-R in multiple Vietnamese-specific NLP tasks. |
| Approach: | They present PhoBERT with two versions, Phobert-base and PhoBRET-large, which are pre-trained for Vietnamese. |
| Outcome: | The proposed model outperforms the best pre-trained model XLM-R and improves the state-of-the-art in multiple Vietnamese-specific NLP tasks including Part-of speech tagging, Dependency parsing, Named-entity recognition and Natural language inference. |
Calibrating Structured Output Predictors for Natural Language Processing (2020.acl-main)
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| Challenge: | Several modern machine-learning based NLP systems can provide a confidence score with their output predictions. |
| Approach: | They propose a general calibration scheme for output entities of interest in NLP applications that can be used to calibrate confidence scores. |
| Outcome: | The proposed calibration scheme outperforms current calibration techniques for Named Entity Recognition, Part-of-speech tagging and Question Answering systems. |
Evaluating morphological typology in zero-shot cross-lingual transfer (2021.acl-long)
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| Challenge: | morphological typology has been used to improve cross-lingual transfer . however, some language families and typologies consistently perform worse . |
| Approach: | They examine effects of morphological typology on zero-shot cross-lingual transfer . they perform part-of-speech tagging and sentiment analysis on 19 languages . |
| Outcome: | The proposed model improves on fusional and introflexive languages, but some language families and typologies perform worse. |