<ul><li>Late chunking is a query-driven segmentation technique that allows more flexible and dynamic document segmentation at retrieval time based on the query.</li><li>Late chunking provides distinct advantages over traditional early chunking methods, including better contextual awareness, reduced indexing overhead, better query adaptability, and improved performance of language and learning models (LLMs).</li><li>Optimizations to enhance the efficiency of late chunking include efficient embedding retrieval, adaptive windowing, vector pruning, parallelized late chunking, and re-ranking with LLMs.</li><li>Late chunking is particularly effective in domains such as enterprise knowledge management, legal document search, medical Q&A systems, technical support chatbots, and scientific research assistants.</li></ul>

Late Chunking in LLM Pipelines: A Deep Dive into Optimized Text Retrieval

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