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A carefully curated collection of papers related to large model systems, covering training, inference, multimodality, and more. It is continuously updated and includes technical reports, frameworks, and courses, making it a valuable reference for researchers and developers.
LLMSys-PaperList is a curated reading list on GitHub that organizes LLM systems research papers and resources into practical categories such as training systems, serving systems, and multi-modal coverage, helping AI/ML engineers and researchers stay updated.
The article highlights a critical failure mode in production RAG systems where confident but incorrect answers arise from versioning issues and lack of uncertainty mechanisms. It proposes architectural improvements like routing layers, retrieval scoring, and hallucination checks to mitigate these errors.