mlsanityData to 13 Oct 2026

Unleashing the Potential of Large Language Models: A Blueprint for Real-Time, Enterprise-Ready Deployments

arXiv 2608.00419 ↗First posted 1 Aug 2026cs.LG cs.AI cs.CLcited by 0

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Abstract (arXiv)

Large language models deployed in real-time, regulated settings face knowledge staleness, catastrophic forgetting, hallucination, and weak feedback loops. We present a unified, pattern-driven LLMOps architecture integrating real-time data ingestion, continual learning, retrieval-augmented generation (RAG), and human-in-the-loop feedback into a single operational pipeline. Four contributions map to established software design patterns: an adaptive ingestion pattern orchestrator (AIPO) evaluated with FreshStreamBench; STAR+FAR continual learning with sparse temporal adapter routing and freshness-aware replay; SAGE, an SLO-aware adaptive retrieval policy predicting a per-query passage budget to meet tail-latency targets; and an automated feedback-driven convergence stage with RLHF triggers. The result reduces latency-cost-accuracy trade-offs while supporting auditability and rollback for high-risk sectors such as health care and finance.

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References · 10

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,304
  2. 2020Language Models are Few-Shot Learnerscited by 32,320
  3. 2023GPT-4 Technical Reportcited by 18,278
  4. 2022Training language models to follow instructions with human feedbackcited by 15,856
  5. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,221
  6. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,317
  7. 2021On the Opportunities and Risks of Foundation Modelscited by 3,999
  8. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,594
  9. 2024Is Your LLM Outdated? A Deep Look at Temporal Generalizationcited by 26
  10. 2023AutoHall: Automated Factuality Hallucination Dataset Generation for Large Language Modelscited by 10

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  3. 2024A critical review of methods and challenges in large language models
  4. 2024InfiniPot: Infinite Context Processing on Memory-Constrained LLMs
  5. 2023Improving Language Models via Plug-and-Play Retrieval Feedback
  6. 2025Continual Learning of Domain Knowledge from Human Feedback in Text-to-SQL
  7. 2025Memory in Large Language Models: Mechanisms, Evaluation and Evolution
  8. 2025OkraLong: A Flexible Retrieval-Augmented Framework for Long-Text Query Processing