5 papers · 1 filter
HeadlineCause: A Dataset of News Headlines for Detecting Causalities
Ilya Gusev, Alexey Tikhonov
Detecting implicit causal relations in texts is a task that requires both common sense and world knowledge. Existing datasets are focused either on commonsense causal reasoning or…
Russian News Clustering and Headline Selection Shared Task
Ilya Gusev, Ivan Smurov
This paper presents the results of the Russian News Clustering and Headline Selection shared task. As a part of it, we propose the tasks of Russian news event detection, headline s…
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…
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…
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…