3 papers
cs.CL2020
Advances of Transformer-Based Models for News Headline Generation
Alexey Bukhtiyarov, Ilya Gusev
Pretrained language models based on Transformer architecture are the reason for recent breakthroughs in many areas of NLP, including sentiment analysis, question answering, named e…
cs.CL2019
Importance of Copying Mechanism for News Headline Generation
Ilya Gusev
News headline generation is an essential problem of text summarization because it is constrained, well-defined, and is still hard to solve. Models with a limited vocabulary can not…
cs.CL2018
Improving part-of-speech tagging via multi-task learning and character-level word representations
Daniil Anastasyev, Ilya Gusev, Eugene Indenbom
In this paper, we explore the ways to improve POS-tagging using various types of auxiliary losses and different word representations. As a baseline, we utilized a BiLSTM tagger, wh…