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RETA-LLM

RETA-LLM is a toolkit designed for retrieval-augmented large language models. It is directly relevant to vector databases as it involves retrieval-based methods that typically leverage vector search and vector databases to enhance language model capabilities through external knowledge retrieval.

MyScale's Vector Database Benchmark

Benchmark results and tools by MyScale aimed at measuring the performance of vector databases in various search and retrieval tasks.

ACL 2023 Tutorial: Retrieval-Based Language Models and Applications

This ACL 2023 tutorial reviews retrieval-based language models, which often rely on vector databases and vector search systems to retrieve relevant context. The tutorial covers methods and applications central to the use of vector databases in modern NLP systems.

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