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Vision-language-action models under parallel intelligence paradigm: the state of the art and future perspectives
Papers and Reports | 更新时间：2025-11-18
|
Vision-language-action models under parallel intelligence paradigm: the state of the art and future perspectives
- Chinese Journal of Intelligent Science and Technology Vol. 7, Issue 3, Pages: 290-303(2025)
- 作者机构：
1.华东师范大学通信与电子工程学院，上海 200241
2.湖南大学机械与运载工程学院，湖南 长沙 410082
3.澳门科技大学创新工程学院，澳门 999078
4.中国科学院自动化研究所多模态人工智能系统全国重点实验室，北京 100190
5.麻省理工学院信息与决策系统实验室，剑桥 02139-4307
- 作者简介：
- 基金信息：Science and Technology Development Fund, Macao Special Administrative Region(0157/2024/RIA2;0093/2023/RIA2;0145/2023/RIA3);The National Natural Science Foundation of China(62103139);Lotus Youth Talent Program of Hunan Province(2023RC3115)
DOI：10.11959/j.issn.2096-6652.202536
CLC： TP391.4Received：02 August 2025，
Revised：2025-09-16，
Accepted：18 September 2025，
Published：15 September 2025
- 稿件说明：
移动端阅览
李柏,郝金第,孙跃硕等.平行智能范式视角下的视觉-语言-动作模型发展现状与展望[J].智能科学与技术学报,2025,07(03):290-303.
LI Bai,HAO Jindi,SUN Yueshuo,et al.Vision-language-action models under parallel intelligence paradigm: the state of the art and future perspectives[J].Chinese Journal of Intelligent Science and Technology,2025,07(03):290-303.
李柏,郝金第,孙跃硕等.平行智能范式视角下的视觉-语言-动作模型发展现状与展望[J].智能科学与技术学报,2025,07(03):290-303. DOI： 10.11959/j.issn.2096-6652.202536.
LI Bai,HAO Jindi,SUN Yueshuo,et al.Vision-language-action models under parallel intelligence paradigm: the state of the art and future perspectives[J].Chinese Journal of Intelligent Science and Technology,2025,07(03):290-303. DOI： 10.11959/j.issn.2096-6652.202536.
Vision-language-action models under parallel intelligence paradigm: the state of the art and future perspectives
摘要
视觉-语言-动作模型是一类面向具身智能的综合性建模方法，它将视觉感知、自然语言理解和动作执行在统一框架下进行表征与学习，旨在实现从环境感知到任务规划再到动作控制的连续闭环。视觉-语言-动作模型的运行逻辑与21世纪初提出的平行智能范式存在呼应。平行智能通过“人工系统、计算实验和平行执行”的三元架构，强调虚拟建模、可复现推演以及虚实交互的闭环机制，这些理念与视觉-语言-动作模型的发展路径在不同阶段形成了对应关系：早期的多模态探索可视为人工系统中的原型实践，随后的大规模模型与跨域训练扩展了计算实验的能力，近年来的分层控制和虚实闭环则体现了平行执行强调的反馈修正与规范指导。在这一框架下，视觉-语言-动作模型呈现出语义与动作深度耦合、虚拟与现实双向循环和可验证性增强等特征，但也存在泛化不足、语义对齐不稳、安全与解释机制薄弱以及部署效率受限等问题。未来研究可聚焦任务语义的契约化表达、长时序规划的可修复性、世界模型的工程化使用、多层次反馈与安全治理，以及跨平台迁移和人机协作等方向。以平行智能为参照重新审视视觉-语言-动作模型，不仅有助于厘清发展脉络，也为其在真实场景中的可信应用提供了方法论支持。
Abstract
Vision-language-action (VLA) models are a comprehensive modeling approach for embodied intelligence that integrates visual perception
natural language understanding
and action execution within a unified framework
aiming to establish a continuous loop from environmental perception to task planning and action control. Their operational logic corresponds closely to the paradigm of parallel intelligence articulated in the early 21st century. That paradigm comprises artificial systems
computational experiments
and parallel execution
emphasizing virtual modeling
reproducible inference
and closed-loop interaction between the virtual and the real. The initial stage of VLA development
driven by multimodal deep learning
can be regarded as prototypical work within artificial systems
the subsequent stage characterized by large-scale models and cross-domain training expanded the scope of computational experiments
and the more recent focus on hierarchical control and virtual-real closed loops reflects the feedback correction and normative guidance emphasized in parallel execution. VLA models exhibit deep coupling between semantics and action
iterative cycles linking simulation with reality
and steadily improving verifiability. Nonetheless
challenges remain in generalization
semantic alignment
safety and interpretability
and deployment efficiency. Addressing these issues calls for contract-based task semantics
repairable long-horizon hierarchical planning
engineering-oriented use of world models
multi-level feedback and safety governance
and cross-platform transfer with human-machine collaboration. Examining VLA through the lens of parallel intelligence clarifies its developmental logic and provides methodological support for advancing toward trustworthy real-world applications.
关键词
Keywords
references
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