Large Language Models (LLMs) have shown extraordinary capabilities in understanding
and generating text that closely mirrors human communication. However, a primary …

Knowledge editing has been increasingly adopted to correct the false or outdated
knowledge in Large Language Models (LLMs). Meanwhile, one critical but under-explored …

Modern language models have the capacity to store and use immense amounts of
knowledge about real-world entities, but it remains unclear how to update such knowledge …

Large multimodal language models have proven transformative in numerous applications.
However, these models have been shown to memorize and leak pre-training data, raising …

Fine-tuning large language models (LLMs) on additional datasets is often necessary to
optimize them for specific downstream tasks. However, existing safety alignment measures …

The model editing problem concerns how language models should learn new facts about
the world over time. While empirical research on model editing has drawn widespread …

Large language model (LLM) based agents have recently attracted much attention from the
research and industry communities. Compared with original LLMs, LLM-based agents are …

The advent of Large Language Models (LLMs) has garnered significant popularity and
wielded immense power across various domains within Natural Language Processing …

Motivated by the transformative capabilities of large language models (LLMs) across various
natural language tasks, there has been a growing demand to deploy these models …

Abstraction ability is crucial in human intelligence, which can also benefit various tasks in
NLP study. Existing work shows that LLMs are deficient in abstract ability, and how to …