Natural language processing (NLP) technologies and applications in legal text processing
are gaining momentum. Being one of the most prominent tasks in NLP, named-entity …

The processing of legal texts has been developing as an emerging field in natural language
processing (NLP). Legal texts contain unique jargon and complex linguistic attributes in …

It is widely assumed that gendered wording in job advertisements can be a source of
unconscious gender bias that contributes to occupational gender segregation, and gender …

Transformer-based contextualized language models constitute the state-of-the-art in several
natural language processing (NLP) tasks and applications. Despite their utility …

In the fast-evolving domain of artificial intelligence, large language models (LLMs) such as
GPT-3 and GPT-4 are revolutionizing the landscapes of finance, healthcare, and law …

Data derived from the realm of the social sciences is often produced in digital text form,
which motivates its use as a source for natural language processing methods. Researchers …

Static word embeddings are ubiquitous in computational social science applications and
contribute to practical decision-making in a variety of fields including law and healthcare …

While large language models (LLMs) exhibit impressive performance on a wide range of
NLP tasks, most of them fail to learn the causality from correlation, which disables them from …

Natural Language Processing (NLP) based approaches have recently become very popular
for studies in legal domain. In this work, the outcomes of the cases of the Court of Cassation …

Hate speech against individuals or communities with different backgrounds is a major
problem in online social networks. The domain of hate speech has spread to various topics …