Following this, the introduction of large language models (LLMs) such as GPT-4 and BERT has lifted the standard for this task, promoting them to new heights of performance and capacity. Our survey provides a de
因此,将 LLM 作为智能体部署到复杂环境中面临若干关键挑战:1)基于 LLM 的智能体在长期规划和多步骤推理方面存在困难,因为其生成内容可能导致任务不一致性或错误的累积,尤其是在长期交互中;2)LLM 的有限记忆容量阻碍了智能体利用过去的经验进行反思,导致决策和任务性能不理想;3)基于 LLM 的智能体对新环境的适应能力...
A Survey of LLM × DATA A collection of papers and projects related to LLMs and corresponding data-centric methods. If you find our survey useful, please cite the paper:@article{LLMDATASurvey, title={A Survey of LLM × DATA}, author={Xuanhe Zhou, Junxuan He, Wei Zhou, Haodong Chen,...
Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely 摘要 外部数据增强的大语言模型 (LLM) 在完成真实世界任务方面表现出令人印象深刻的能力。外部数据不仅增强了模型的领域专业知识和时间相关性,而且减少了幻觉的发生率,从而提高了输出...
A Survey of LLM Surveys Large language models (LLMs) are making sweeping advances across many fields of artificial intelligence. As a result, research interest and progress in LLMs have exploded. There are now hundreds of research papers on LLMs published in various conferences or posted to ope...
Recently, through the acquisition of vast amounts of Web knowledge, large language models (LLMs) have shown potential in human-level intelligence, leading to a surge in research on LLM-based autonomous agents. In this paper, we present a comprehensive survey of these studies, delivering a ...
To the best of our knowledge, our survey is the first to cover all three key aspects related to security and privacy for the first time. Second, we have made several interesting discoveries. For instance, our research reveals that LLMs contribute more positively than negatively to security and...
Typically,large language models (LLMs)refer to Transformer language models that containhundreds of billions (or more) of parameters, which are trained on massive text data [32], such as GPT-3 [55], PaLM [56], Galactica [35], and LLaMA [57]. LLMs exhibit strong capacities to understand...
Career Essentials in Generative AI by Microsoft and LinkedIn is a free course source. It helps to understand the Essentials in Generative AI. The exam is challenging. I decided to solve it with ChatGPT. And the final score is 83.
Building upon these strengths, researchers have begun incorporating LLMs into multi-agent systems (MAS), where agents collaborate or compete through natural language interactions to tackle tasks beyond the scope of single-agent setups. In this survey, we present a communication-centric perspective on...