This paper focuses on paraphrase generation, which is a widely studied natural language
generation task in NLP. With the development of neural models, paraphrase generation …

A major challenge in paraphrase research is the lack of parallel corpora. In this paper, we
present a new method to collect large-scale sentential paraphrases from Twitter by linking …

Current lexical simplification approaches rely heavily on heuristics and corpus level features
that do not always align with human judgment. We create a human-rated word-complexity …

The growing prominence of large language models, such as GPT-4 and ChatGPT, has led to
increased concerns over academic integrity due to the potential for machine-generated …

In this paper, we introduce the first fully manually annotated paraphrase corpus for Finnish
containing 53,572 paraphrase pairs harvested from alternative subtitles and news headings …

Sequence-to-sequence paraphrase generation models often struggle with the generation of
diverse paraphrases. This deficiency constrains the viability of leveraging paraphrase …

In this paper, we study natural language paraphrasing from both corpus creation and
modeling points of view. We focus in particular on the methodology that allows the extraction …

In the realm of text manipulation and linguistic transformation, the question of authorship has
always been a subject of fascination and philosophical inquiry. Much like the\textbf {Ship of …

Paraphrase generation reflects the ability to understand the meaning from the language
surface form and rephrase it to other expressions. Recent paraphrase generation works …

As natural language processing research is growing and largely driven by the availability of
data, we expanded research from news and small-scale dialog corpora to web and social …