Large language models (LLMs) often exhibit deficient reasoning or generate hallucinations.
To address these, studies prefixed with" Self-" such as Self-Consistency, Self-Improve, and …

Refusal-Aware Instruction Tuning (RAIT) aims to enhance Large Language Models (LLMs)
by improving their ability to refuse responses to questions beyond their knowledge, thereby …

Role-Playing Agents (RPAs) have shown remarkable performance in various applications,
yet they often struggle to recognize and appropriately respond to hard queries that conflict …

Multimodal large language models (MLLMs) excel at multimodal perception and
understanding, yet their tendency to generate hallucinated or inaccurate responses …

While large language models (LLMs) encode vast amounts of knowledge within their
parameters for some mainstream entities, factual inconsistencies and untruthfulness in LLMs …

Large language models (LLM) have made significant achievements in the field of natural
language processing, but the generated text often contains content that is inconsistent with …