Recent studies report that autoregressive language models can successfully solve many
NLP tasks via zero-and few-shot learning paradigms, which opens up new possibilities for …

The impressive capabilities of recent generative models to create texts that are challenging
to distinguish from the human-written ones can be misused for generating fake news …

To enhance the quality of generated stories, recent story generation models have been
investigating the utilization of higher-level attributes like plots or commonsense knowledge …

Nowadays, Transformer language models (LMs) represent a fundamental component of the
NLP research methodologies and applications. However, the development of such models …

Recent studies have suggested that neural language models learn and store a large amount
of facts and commonsense knowledge from training data. The ability of language models to …

The development of automated approaches to linguistic acceptability has been greatly
fostered by the availability of the English CoLA corpus, which has also been included in the …

The application of deep learning methods to problems in natural language processing has
generated significant progress across a wide range of natural language processing tasks …

Linguistic acceptability (LA) attracts the attention of the research community due to its many
uses, such as testing the grammatical knowledge of language models and filtering …

Neural network language models appear to be increasingly aligned with how humans
process and generate language, but identifying their weaknesses through adversarial …

Adjunct clauses are traditionally assumed to be strong islands for extraction across
languages. However, the universal island status of adjunct clauses has been challenged by …