Tinkoff Researchers Unveil ReBased: Pioneering Machine Learning with Enhanced Subquadratic Architectures for Superior In-Context Learning

New standards are being set across various activities by Large Language Models (LLMs), which are causing a revolution in natural language processing. Despite their successes, most of these models rely on attention mechanisms implemented in Transformer frameworks. Impractical computing complexity for extending contextual processing is caused by these techniques, which scale poorly with large text […]

The post Tinkoff Researchers Unveil ReBased: Pioneering Machine Learning with Enhanced Subquadratic Architectures for Superior In-Context Learning appeared first on MarkTechPost.

ai shorts applications architectures artificial intelligence attention attention mechanisms complexity computing context editors pick frameworks in-context learning language language models language processing large language large language models llms machine machine learning natural natural language natural language processing processing researchers set staff standards tech news technology transformer