This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …

The rapid advancement of Large Language Models (LLMs) has attracted much attention to
value alignment for their responsible development. However, how to define values in this …

Large language models (LLMs) often encounter knowledge conflicts, scenarios where
discrepancy arises between the internal parametric knowledge of LLMs and non-parametric …

Designing systems that can reason across cultures requires that they are grounded in the
norms of the contexts in which they operate. However, current research on developing …

While existing alignment paradigms have been integral in developing large language
models (LLMs), LLMs often learn an averaged human preference and struggle to model …

The development of large language models has instilled widespread interest among the
researchers to understand their inherent reasoning and problem-solving capabilities …

Objective: An ethical framework for the use of large language models (LLMs) is urgently
needed to shape how natural language processing (NLP) tools are used for healthcare …

Although humans inherently have diverse values, current large language model (LLM)
alignment methods often assume that aligning LLMs with the general public's preferences is …

Large language models are limited by challenges in factuality and hallucinations to be
directly employed off-the-shelf for judging the veracity of news articles, where factual …

Large Language Models (LLMs) have demonstrated exceptional task-solving capabilities,
increasingly adopting roles akin to human-like assistants. The broader integration of LLMs …