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English(EN) A Survey on Foundations and Frontiers of Multimodal Agentic Frameworks: Techniques and Applications

综述详述多模态智能体框架及其应用

一篇新的综述论文探讨了多模态智能体框架的演变和影响,这些框架将大型语言模型(LLMs)与图像、音频和视频等不同数据类型集成。该论文分析了多模态如何增强智能体在感知、推理、规划、记忆和行动方面的能力。它根据现有系统的架构选择对其进行分类,并回顾了其在机器人、网页导航和内容生成等领域的应用,同时讨论了性能和效率的权衡。 AI

影响 提供了多模态智能体框架的结构化概述,帮助研究人员和开发人员理解当前能力和未来方向。

排序理由 该条目是发表在arXiv上的综述论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

综述详述多模态智能体框架及其应用

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该条目是发表在arXiv上的综述论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Neel Mokaria, Rishie Raj, Dheeraj Baiju, Xiaoqian Shen, Shraman Pramanick, Kevin Qinghong Lin, Arda Senocak, Mike Zheng Shou, Philip Torr, Mohamed Elhoseiny, Yapeng Tian, Ruohan Gao, Salman Khan, Sayan Nag, Sanjoy Chowdhury, Dinesh Manocha ·

    多模态代理框架基础与前沿:技术与应用综述

    arXiv:2608.20379v1 Announce Type: new Abstract: Advances in large language models (LLMs) have fueled a wave of research into agency: the ability to reason, plan, and act. This effort has produced agentic frameworks that orchestrate perception, memory, and decision-making around p…