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(DongIpix/Shutterstock If you’re using a large language model (LLM) to develop a generative AI application, chances are pretty good that a vector database is somewhere in the mix. When it comes time to choose a vector database, there are plenty of options, and the biggest choice may be whether to go with a dedicated vector database or use an existing relational or NoSQL data store that has added vector storage and serving capabilities. Vector databases have emerged as critical components for building GenAI applications, such as chatbots, AI agents, and question-answering systems. They’re important because they allow organizations to store…

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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

arXiv:2406.14721v1 Announce Type: new Abstract: Large Language Models (LLMs) have garnered significant attention due to their remarkable ability to process information across various languages. Despite their capabilities, they exhibit inconsistencies in handling identical queries in different languages, presenting challenges for further advancement. This paper introduces a method to enhance the multilingual performance of LLMs by aggregating knowledge from diverse languages. This approach incorporates a low-resource knowledge detector specific to a language, a language selection process, and mechanisms for answer replacement and integration. Our experiments demonstrate notable performance improvements, particularly in reducing language performance disparity. An ablation study confirms that each…