Large language models (LLMs) demonstrate powerful capabilities, but they still face
challenges in practical applications, such as hallucinations, slow knowledge updates, and …

As large language models continue to develop in the field of AI, text generation systems are
susceptible to a worrisome phenomenon known as hallucination. In this study, we …

Training large language models (LLMs) with open-domain instruction following data brings
colossal success. However, manually creating such instruction data is very time-consuming …

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

Training large language models (LLMs) with open-domain instruction following data brings
colossal success. However, manually creating such instruction data is very time-consuming …

Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of
AI, both in research and commerce. Through instruction-tuning a large language model …

Large language models (LLMs) have revolutionized numerous domains with their
impressive performance but still face their challenges. A predominant issue is the propensity …

We present chain-of-knowledge (CoK), a novel framework that augments large language
models (LLMs) by dynamically incorporating grounding information from heterogeneous …

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

Continual learning (CL) is a paradigm that aims to replicate the human ability to learn and
accumulate knowledge continually without forgetting previous knowledge and transferring it …