Large language models (LLMs) have demonstrated remarkable capabilities across a wide
range of tasks in various domains. Despite their impressive performance, they can be …

The increased use of large language models (LLMs) across a variety of real-world
applications calls for mechanisms to verify the factual accuracy of their outputs. In this work …

In the age of large language models (LLMs) and the widespread adoption of AI-driven
content creation, the landscape of information dissemination has witnessed a paradigm shift …

The NLP community has recently shown a growing interest in leveraging Large Language
Models (LLMs) for knowledge-intensive tasks, viewing LLMs as potential knowledge bases …

The dissemination of false information on online platforms presents a serious societal
challenge. While manual fact-checking remains crucial, Large Language Models (LLMs) …

Hallucination has emerged as the most vulnerable aspect of contemporary Large Language
Models (LLMs). In this paper, we introduce the Sorry, Come Again (SCA) prompting, aimed …

As we all know, hallucinations prevail in Large Language Models (LLMs), where the
generated content is coherent but factually incorrect, which inflicts a heavy blow on the …

The increased use of large language models (LLMs) across a variety of real-world
applications calls for mechanisms to verify the factual accuracy of their outputs. Difficulties lie …

The increased use of large language models (LLMs) across a variety of real-world
applications calls for automatic tools to check the factual accuracy of their outputs, as LLMs …

We introduce Loki, an open-source tool designed to address the growing problem of
misinformation. Loki adopts a human-centered approach, striking a balance between the …