Automatic elicitation of semantic information from natural language texts is an important
research problem with many practical application areas. Especially after the recent …

Media bias, ie, slanted news coverage, can strongly impact the public perception of the
reported topics. In the social sciences, research over the past decades has developed …

Despite widespread use of LLMs as conversational agents, evaluations of performance fail
to capture a crucial aspect of communication: interpreting language in context …

We present an analytic study on the language of news media in the context of political fact-
checking and fake news detection. We compare the language of real news with that of satire …

We consider the task of text attribute transfer: transforming a sentence to alter a specific
attribute (eg, sentiment) while preserving its attribute-independent content (eg, changing" …

Massive dissemination of fake news and its potential to erode democracy has increased the
demand for accurate fake news detection. Recent advancements in this area have proposed …

Many text corpora exhibit socially problematic biases, which can be propagated or amplified
in the models trained on such data. For example, doctor cooccurs more frequently with male …

Misinformation such as fake news is one of the big challenges of our society. Research on
automated fact-checking has proposed methods based on supervised learning, but these …

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 …

We can often detect from a person's utterances whether he or she is in favor of or against a
given target entity—one's stance toward the target. However, a person may express the …