Papers by Dmitrii Aksenov

1 papers
Abstractive Text Summarization based on Language Model Conditioning and Locality Modeling (2020.lrec-1)

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Challenge: Abstractive summarization is an NLP task with many real-world applications.
Approach: They propose to use a pre-trained language model to train a Transformer-based neural model . they propose a new method of BERT-windowing to allow chunk-wise processing of texts longer than the BERT window size .
Outcome: The proposed model outperforms baseline models on CNN/Daily Mail dataset and shows its superiority on German dataset.

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