Large pre-trained language models (PLMs) have been shown to retain implicit knowledge
within their parameters. To enhance this implicit knowledge, we propose Knowledge …

Textual knowledge bases such as Wikipedia require considerable effort to keep up to date
and consistent. While automated writing assistants could potentially ease this burden, the …

Much of modern-day text simplification research focuses on sentence-level simplification,
transforming original, more complex sentences into simplified versions. However, adding …

Datasets for data-to-text generation typically focus either on multi-domain, single-sentence
generation or on single-domain, long-form generation. In this work, we cast generating …

Event data, or structured records of``who did what to whom''that are automatically extracted
from text, is an important source of data for scholars of international politics. The high cost of …

In the task of entity description generation, given a context and a specified entity, a model
must describe that entity correctly and in a contextually-relevant way. In this task, as well as …

While large-scale pretrained language models have significantly improved writing
assistance functionalities such as autocomplete, more complex and controllable writing …

Social media datasets make it possible to rapidly quantify collective attention to emerging
topics and breaking news, such as crisis events. Collective attention is typically measured by …

Neural language models have drastically changed the landscape of natural language
processing (NLP). Originally used for language generation (eg, in summarization and …

Recent breakthroughs in Natural Language Processing (NLP) have been driven by
language models trained on a massive amount of plain text. While powerful, deriving …