Due to the considerable growth of the volume of text documents on the Internet and in digital
libraries, manual analysis of these documents is no longer feasible. Having efficient …

Keyphrase extraction is a textual information processing task concerned with the automatic
extraction of representative and characteristic phrases from a document that express all the …

As the amount of generated information grows, reading and summarizing texts of large
collections turns into a challenging task. Many documents do not come with descriptive …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

In this paper, we address the keyphrase extraction problem as sequence labeling and
propose a model that jointly exploits the complementary strengths of Conditional Random …

Recently, the sequence-to-sequence models have made remarkable progress on the task of
keyphrase generation (KG) by concatenating multiple keyphrases in a predefined order as a …

In this work, we explore how to train task-specific language models aimed towards learning
rich representation of keyphrases from text documents. We experiment with different …

Conventional Open Information Extraction (Open IE) systems are usually built on hand-
crafted patterns from other NLP tools such as syntactic parsing, yet they face problems of …

In this paper, we study automatic keyphrase generation. Although conventional approaches
to this task show promising results, they neglect correlation among keyphrases, resulting in …

High-quality phrase representations are essential to finding topics and related terms in
documents (aka topic mining). Existing phrase representation learning methods either …