mlsanityData to 14 Oct 2026

AI Agents and Agentic AI-Navigating a Plethora of Concepts for Future Manufacturing

arXiv 2507.01376 ↗First posted 2 Jul 2025cs.AIcited by 5

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

AI agents are autonomous systems designed to perceive, reason, and act within dynamic environments. With the rapid advancements in generative AI (GenAI), large language models (LLMs) and multimodal large language models (MLLMs) have significantly improved AI agents' capabilities in semantic comprehension, complex reasoning, and autonomous decision-making. At the same time, the rise of Agentic AI highlights adaptability and goal-directed autonomy in dynamic and complex environments. LLMs-based AI Agents (LLM-Agents), MLLMs-based AI Agents (MLLM-Agents), and Agentic AI contribute to expanding AI's capabilities in information processing, environmental perception, and autonomous decision-making, opening new avenues for smart manufacturing. However, the definitions, capability boundaries, and practical applications of these emerging AI paradigms in smart manufacturing remain unclear. To address this gap, this study systematically reviews the evolution of AI and AI agent technologies, examines the core concepts and technological advancements of LLM-Agents, MLLM-Agents, and Agentic AI, and explores their potential applications in and integration into manufacturing, along with the potential challenges they may face.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 16 of its 55 references that are in the map. First posted on arXiv 2 Jul 2025.

Builds on

16 of 55 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024Large Multimodal Agents: A Survey23 Feb
  2. 2023A Survey on Large Language Model based Autonomous Agents22 Aug

Other references · 14

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  4. 2023Improved Baselines with Visual Instruction Tuningcited by 4,418
  5. 2023Qwen Technical Reportcited by 3,344
  6. 2023PaLM-E: An Embodied Multimodal Language Modelcited by 2,071
  7. 2023A Survey on Multimodal Large Language Modelscited by 909
  8. 2023The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)cited by 681
  9. 2023mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaborationcited by 547
  10. 2022LayoutLMv3: Pre-training for Document AI with Unified Text and Image Maskingcited by 485
  11. 2023Towards Generalist Biomedical AIcited by 289
  12. 2023Multimodal Large Language Models: A Surveycited by 195
2 more
  1. 2023Art and the science of generative AI: A deeper divecited by 95
  2. 2022XYLayoutLM: Towards Layout-Aware Multimodal Networks For Visually-Rich Document Understandingcited by 68

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2025Getting out of the Big-Muddy: Escalation of Commitment in LLMscited by 1
  2. 2026Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challengescited by 1
  3. 2026An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computingcited by 1
  4. 2026Hierarchical Prompt-Domain Control and Learning for Resource-Constrained Agentic Language Modelscited by 0
  5. 2026Agentic AI Autonomy Assessment: A Decision-Support Framework Towards Governed Supply Chain Systemscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents
  2. 2023The Rise and Potential of Large Language Model Based Agents: A Survey
  3. 2025Fundamentals of Building Autonomous LLM Agents
  4. 2025LLM-Powered AI Agent Systems and Their Applications in Industry
  5. 2025From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users
  6. 2025Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction
  7. 2025From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review
  8. 2025A Survey on Agentic Multimodal Large Language Models