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Andrew L Maas, Raymond E Daly, Peter T Pham, Dan Huang, Andrew Y Ng, and Christopher Potts. 2011. Learning word vectors for sentiment analysis. In ACL. Association for Computational Linguistics, 142--150. Google Scholar; Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. [n. d.] Pointer sentinel mixture models.

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Sentiment analysis is one of numerous text analysis techniques of DiscoverText. IBM Watson Natural Language Understanding is a set of advanced text analytics systems. Analyzing text with this service, users can extract such metadata as concepts, entities, keywords, as well as categories and relationships. # application: machine translation, sentiment analysis, question answering. # technology: self-attention, Transformer, pretrained language models. # toolkits: Fairseq, Huggingface. Tháng 7/2020, anh và VinAI đã công bố paper: PhoBERT: The first public large-scale language models for Vietnamese và chia sẻ rộng rãi trong cộng đồng.

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The quadratic computational and memory complexities of the Transformer's attention mechanism have limited its scalability for modeling long sequences. In this paper, we propose Luna, a linear unified nested attention mechanism that approximates softmax attention with two nested linear attention functions, yielding only linear (as opposed to quadratic) time and space complexity. As compared ...BERTweet is the first public large-scale language model pre-trained for English Tweets. BERTweet is trained based on the RoBERTa pre-training procedure, using the same model configuration as BERT-base. The corpus used to pre-train BERTweet consists of 850M English Tweets (16B word tokens ~ 80GB), containing 845M Tweets streamed from 01/2012 to ...

Text Summarization. Text summarization is the process of distilling the most important information from a source text to produce an abridged version for a particular user and task .