mlsanityData to 7 Oct 2026

An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applications

arXiv 2306.02781 ↗First posted 5 Jun 2023cs.LG cs.AIcited by 20

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Abstract (arXiv)

Generative artificial intelligence, and large language models in particular, have emerged as one of the most transformative paradigms in modern computer science. This automated survey provides an accessible treatment of the field as of early 2026, with a strong focus on the leading model families, deployment protocols, and real-world applications. The core of the survey is devoted to a detailed comparative analysis of the frontier large language models, with particular emphasis on open-weight systems: DeepSeek-V3, DeepSeek-R1, DeepSeek-V3.2, and the forthcoming DeepSeek V4; the Qwen 3 and Qwen 3.5 series; GLM-5; Kimi K2.5; MiniMax M2.5; LLaMA 4; Mistral Large 3; Gemma 3; and Phi-4, alongside proprietary systems including GPT-5.4, Gemini 3.1 Pro, Grok 4.20, and Claude Opus 4.6. For each model, we describe the architectural innovations, training regimes, and empirical performance on current benchmarks and the Chatbot Arena leaderboard. The survey further covers deployment protocols including Retrieval-Augmented Generation, the Model Context Protocol, the Agent-to-Agent protocol, function calling standards, and serving frameworks. We present an extensive review of real-world applications across fifteen industry sectors, from financial services and legal technology to tourism and agriculture, supported by empirical evidence and case studies. This work has been generated by Claude Opus 4.6 (Anthropic) under the supervision and editorial review of the human authors, with the goal of producing updated editions approximately every six months.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 20 of its 128 references that are in the map. First posted on arXiv 5 Jun 2023.

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20 of 128 references.

References · 20

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8 more
  1. 2020GLU Variants Improve Transformercited by 1,724
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Citing papers per year: 2023: 5; 2024: 4; 2025: 10; 2026: 1.

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  1. 2024SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compressioncited by 231
  2. 2025SVD-LLM V2: Optimizing Singular Value Truncation for Large Language Model Compressioncited by 63
  3. 2023Model-as-a-Service (MaaS): A Surveycited by 24
  4. 2024A Philosophical Introduction to Language Models - Part II: The Way Forwardcited by 17
  5. 2023MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systemscited by 14
  6. 2025Generative Models in Decision Making: A Surveycited by 14
  7. 2024An Agentic Approach to Automatic Creation of P&ID Diagrams from Natural Language Descriptionscited by 12
  8. 2023Harnessing LLM to Attack LLM-Guarded Text-to-Image Modelscited by 10
  9. 2023Diffusion Models for Generative Artificial Intelligence: An Introduction for Applied Mathematicianscited by 5
  10. 2025Generative AI in Depth: A Survey of Recent Advances, Model Variants, and Real-World Applicationscited by 5
  11. 2025Learning an Efficient Optimizer via Hybrid-Policy Sub-Trajectory Balancecited by 5
  12. 2024Speech to Reality: On-Demand Production using Natural Language, 3D Generative AI, and Discrete Robotic Assemblycited by 4
8 more
  1. 2025Infogen: Generating Complex Statistical Infographics from Documentscited by 2
  2. 2025On-device System of Compositional Multi-tasking in Large Language Modelscited by 2
  3. 2025Towards autonomous normative multi-agent systems for Human-AI software engineering teamscited by 2
  4. 2023Best uses of ChatGPT and Generative AI for computer science researchcited by 1
  5. 2025GenAI-based Multi-Agent Reinforcement Learning towards Distributed Agent Intelligence: A Generative-RL Agent Perspectivecited by 1
  6. 2025Elementary Math Word Problem Generation using Large Language Modelscited by 0
  7. 2025Transforming Chatbot Text: A Sequence-to-Sequence Approachcited by 0
  8. 2026Responsible AI for General-Purpose Systems: Overview, Challenges, and A Path Forwardcited by 0

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