Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

Generative AI (GenAI) represents a shift from AI's ability to “recognize” to its ability to
“generate” solutions for a wide range of tasks. As generated solutions and applications grow …

While large language models (LLMs) have demonstrated remarkable capabilities across a
range of downstream tasks, a significant concern revolves around their propensity to exhibit …

Large language models (LLMs) have demonstrated impressive capabilities in natural
language processing. However, their internal mechanisms are still unclear and this lack of …

Machine learning models are widely used, but can also often be wrong. Users would benefit
from a reliable indication of whether a given output from a given model should be trusted, so …

Uncertainty decomposition refers to the task of decomposing the total uncertainty of a model
into data (aleatoric) uncertainty, resulting from the inherent complexity or ambiguity of the …

Large Language Model (LLM) systems are inherently compositional, with individual LLM
serving as the core foundation with additional layers of objects such as plugins, sandbox …

Confidence estimation aiming to evaluate output trustability is crucial for the application of
large language models (LLM), especially the black-box ones. Existing confidence estimation …

The proliferation of open-source Large Language Models (LLMs) from various institutions
has highlighted the urgent need for comprehensive evaluation methods. However, current …

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