mlsanityData to 14 Oct 2026

MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems

arXiv 2508.21307 ↗First posted 29 Aug 2025cs.AIcited by 0

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Abstract (arXiv)

MultiFluxAI is an innovative AI platform developed to address the challenges of managing and integrating vast, disparate data sources in product engineering across application domains. It addresses both current and new service related queries that enhance user engagement in the digital ecosystem. This platform leverages advanced AI techniques, such as Generative AI, vectorization, and agentic orchestration to provide dynamic and context-aware responses to complex user queries.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 35 of its 43 references that are in the map. First posted on arXiv 29 Aug 2025.

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35 of 43 references.

References · 35

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  3. 2023A Comprehensive Overview of Large Language Modelscited by 648
  4. 2022Improving alignment of dialogue agents via targeted human judgementscited by 531
  5. 2024Large Language Models: A Surveycited by 525
  6. 2024Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexitycited by 451
  7. 2023Fine-Grained Human Feedback Gives Better Rewards for Language Model Trainingcited by 401
  8. 2025Agentic Retrieval-Augmented Generation: A Survey on Agentic RAGcited by 249
  9. 2023CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Servingcited by 203
  10. 2024RAGCache: Efficient Knowledge Caching for Retrieval-Augmented Generationcited by 98
  11. 2024Searching for Best Practices in Retrieval-Augmented Generationcited by 83
  12. 2022Towards Layer-wise Image Vectorizationcited by 79
23 more
  1. 2022Formal Algorithms for Transformerscited by 72
  2. 2024A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directionscited by 70
  3. 2023Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimismcited by 69
  4. 2025Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendationcited by 57
  5. 2022Investigating Explainability of Generative AI for Code through Scenario-based Designcited by 47
  6. 2024WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agentscited by 26
  7. 2024GPT Semantic Cache: Reducing LLM Costs and Latency via Semantic Embedding Cachingcited by 22
  8. 2025Each Graph is a New Language: Graph Learning with LLMscited by 11
  9. 2024Revolutionizing Mental Health Care through LangChain: A Journey with a Large Language Modelcited by 8
  10. 2024A Study on the Implementation Method of an Agent-Based Advanced RAG System Using Graphcited by 8
  11. 2024Comprehensive Study on Sentiment Analysis: From Rule-based to modern LLM based systemcited by 8
  12. 2023Image Vectorization: a Reviewcited by 7
  13. 2024LLM-dCache: Improving Tool-Augmented LLMs with GPT-Driven Localized Data Cachingcited by 7
  14. 2025StreamingRAG: Real-time Contextual Retrieval and Generation Frameworkcited by 4
  15. 2023RETVec: Resilient and Efficient Text Vectorizercited by 3
  16. 2025The Internet of Large Language Models: An Orchestration Framework for LLM Training and Knowledge Exchange Toward Artificial General Intelligencecited by 3
  17. 2025CARING-AI: Towards Authoring Context-aware Augmented Reality INstruction through Generative Artificial Intelligencecited by 3
  18. 2025Context-Aware Semantic Recomposition Mechanism for Large Language Modelscited by 3
  19. 2023Text vectorization via transformer-based language models and n-gram perplexitiescited by 2
  20. 2024A Method for Parsing and Vectorization of Semi-structured Data used in Retrieval Augmented Generationcited by 2
  21. 2024A Multi-LLM Orchestration Engine for Personalized, Context-Rich Assistancecited by 1
  22. 2025CAPRAG: A Large Language Model Solution for Customer Service and Automatic Reporting using Vector and Graph Retrieval-Augmented Generationcited by 1
  23. 2025BEST: A Unified Business Process Enactment via Streams and Tables for Service Computingcited by 1

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