Retrieval-augmented generation for large language models: A survey
Y Gao, Y **ong, X Gao, K Jia, J Pan, Y Bi, Y Dai… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) demonstrate powerful capabilities, but they still face
challenges in practical applications, such as hallucinations, slow knowledge updates, and …
challenges in practical applications, such as hallucinations, slow knowledge updates, and …
Cognitive mirage: A review of hallucinations in large language models
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 …
susceptible to a worrisome phenomenon known as hallucination. In this study, we …
A survey on rag meeting llms: Towards retrieval-augmented large language models
As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …
Graph retrieval-augmented generation: A survey
Recently, Retrieval-Augmented Generation (RAG) has achieved remarkable success in
addressing the challenges of Large Language Models (LLMs) without necessitating …
addressing the challenges of Large Language Models (LLMs) without necessitating …
Retrieval-augmented generation for ai-generated content: A survey
The development of Artificial Intelligence Generated Content (AIGC) has been facilitated by
advancements in model algorithms, scalable foundation model architectures, and the …
advancements in model algorithms, scalable foundation model architectures, and the …
Simple is effective: The roles of graphs and large language models in knowledge-graph-based retrieval-augmented generation
Large Language Models (LLMs) demonstrate strong reasoning abilities but face limitations
such as hallucinations and outdated knowledge. Knowledge Graph (KG)-based Retrieval …
such as hallucinations and outdated knowledge. Knowledge Graph (KG)-based Retrieval …
Retrieval-enhanced knowledge editing for multi-hop question answering in language models
Large Language Models (LLMs) have shown proficiency in question-answering tasks but
often struggle to integrate real-time knowledge updates, leading to potentially outdated or …
often struggle to integrate real-time knowledge updates, leading to potentially outdated or …
Trustworthy, responsible, and safe ai: A comprehensive architectural framework for ai safety with challenges and mitigations
AI Safety is an emerging area of critical importance to the safe adoption and deployment of
AI systems. With the rapid proliferation of AI and especially with the recent advancement of …
AI systems. With the rapid proliferation of AI and especially with the recent advancement of …
Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications
Abstract Knowledge Graph (KG) has attracted more and more companies' attention for its
ability to connect different types of data in meaningful ways and support rich data services …
ability to connect different types of data in meaningful ways and support rich data services …
Topologies of reasoning: Demystifying chains, trees, and graphs of thoughts
M Besta, F Memedi, Z Zhang, R Gerstenberger… - arxiv preprint arxiv …, 2024 - arxiv.org
The field of natural language processing (NLP) has witnessed significant progress in recent
years, with a notable focus on improving large language models'(LLM) performance through …
years, with a notable focus on improving large language models'(LLM) performance through …