# A Survey on Foundations and Frontiers of Multimodal Agentic Frameworks: Techniques and Applications

Published: 2026-08-24 · Updated: 2026-08-24 · Category: Research

Source page: https://www.sipply.dev/story/a-survey-on-foundations-and-frontiers-of-multimodal-agentic-6086e473 · 中文: https://www.sipply.dev/zh/story/a-survey-on-foundations-and-frontiers-of-multimodal-agentic-6086e473

## Summary

A recent survey published on arXiv delves into the advancements and challenges associated with large multimodal models (LMMs) in the context of agentic frameworks. The paper highlights how these models enhance capabilities in reasoning, planning, and acting by integrating various modalities such as text, images, and audio. It also discusses the applications of these frameworks across different domains, emphasizing their potential to improve performance in complex tasks. However, the survey does not shy away from addressing the efficiency challenges and performance metrics that need to be considered for practical implementation.

## Key takeaways

- Large multimodal models significantly enhance agent capabilities in reasoning and planning.
- Integration of different modalities is crucial for improving performance across various applications.
- Efficiency challenges and performance metrics are critical considerations for future developments.

## Why it matters

This survey provides a comprehensive overview of the current landscape of multimodal agentic frameworks, which are essential for advancing AI applications in real-world scenarios. Understanding these frameworks can lead to more effective and versatile AI systems.

- **Product managers:** For product managers, this research highlights the importance of integrating multimodal capabilities into products to enhance user experience and functionality, ensuring that offerings remain competitive in a rapidly evolving market.
- **Developers:** Developers and engineers can leverage insights from this survey to inform their work on multimodal systems, focusing on overcoming efficiency challenges and optimizing performance metrics for better deployment of AI solutions.
- **Students and job seekers:** Students and job-seekers should be aware of the growing significance of multimodal AI frameworks, as expertise in this area could open up numerous career opportunities in research, development, and application of advanced AI technologies.

## Sources

- [A Survey on Foundations and Frontiers of Multimodal Agentic Frameworks: Techniques and Applications](https://arxiv.org/abs/2608.20379) (arXiv cs.AI, 2026-08-24)

## 中文

### 多模态智能框架的基础与前沿调查：技术与应用

最近在arXiv上发布的一项调查深入探讨了与大型多模态模型（LMMs）相关的进展和挑战，特别是在智能框架的背景下。论文强调这些模型通过整合文本、图像和音频等多种模态，增强了推理、规划和行动的能力。它还讨论了这些框架在不同领域的应用，强调其在复杂任务中提高性能的潜力。然而，调查也直面了在实际实施中需要考虑的效率挑战和性能指标。

**要点：**

- 大型多模态模型显著增强了智能体在推理和规划方面的能力。
- 不同模态的整合对提高各类应用的性能至关重要。
- 效率挑战和性能指标是未来发展的关键考虑因素。

**为什么重要：** 这项调查提供了多模态智能框架当前格局的全面概述，这对于推动AI在现实场景中的应用至关重要。理解这些框架可以导致更有效和多功能的AI系统。

---
Sipply: Sip AI News Simply. https://www.sipply.dev