The past decade has witnessed a plethora of works that leverage the power of visualization
(VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML …

The necessity for interpretability in natural language processing (NLP) has risen alongside
the growing prominence of large language models. Among the myriad tasks within NLP, text …

Large Language Models (LLMs) are notorious for blending fact with fiction and generating
non-factual content, known as hallucinations. To address this challenge, we propose an …

Protecting the intellectual property of open-source Large Language Models (LLMs) is very
important, because training LLMs costs extensive computational resources and data …

Neural language models are widely used; however, their model parameters often need to be
adapted to the specific domains and tasks of an application, which is time-and resource …

Over the past years, an increasing number of publications in information visualization,
especially within the field of visual analytics, have mentioned the term “embedding” when …

Large Language Models (LLMs) have revolutionized natural language processing and
demonstrated impressive capabilities in various tasks. Unfortunately, they are prone to …

With a constant increase of learned parameters, modern neural language models become
increasingly more powerful. Yet, explaining these complex model's behavior remains a …

Large Language Models (LLMs) have gained significant attention but also raised concerns
due to the risk of misuse. Jailbreak prompts, a popular type of adversarial attack towards …

The necessity for interpretability in natural language processing (NLP) has risen alongside
the growing prominence of large language models. Among the myriad tasks within NLP, text …