Hallucinations in large language models (LLMs) refer to the phenomenon of LLMs
producing responses that are coherent yet factually inaccurate. This issue undermines the …

This paper introduces Self-aware Knowledge Retrieval (SeaKR), a novel adaptive RAG
model that extracts self-aware uncertainty of LLMs from their internal states. SeaKR activates …

The emergence of Large Language Models (LLMs) has revolutionized how users access
information, shifting from traditional search engines to direct question-and-answer …

Statute retrieval aims to find relevant statutory articles for specific queries. This process is the
basis of a wide range of legal applications such as legal advice, automated judicial …

Utility and topical relevance are critical measures in information retrieval (IR), reflecting
system and user perspectives, respectively. While topical relevance has long been …

In the pursuit of enhancing domain-specific Large Language Models (LLMs), Retrieval-
Augmented Generation (RAG) emerges as a promising solution to mitigate issues such as …

With the rapid development of large-scale language models, Retrieval-Augmented
Generation (RAG) has been widely adopted. However, existing RAG paradigms are …