MIT’s new ‘recursive’ framework lets LLMs process 10 million tokens without context rot

While standard models suffer from context rot as data grows, MIT’s new Recursive Language Model (RLM) framework treats ...
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New 1.5B router model achieves 93% accuracy without costly retraining

Researchers at Katanemo Labs have introduced Arch-Router, a new routing model and framework designed to intelligently map user queries to the most suitable large language model (LLM). For enterprises ...
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A zero-shot learning framework for maize cob phenotyping

A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric traits and estimation of yields in both laboratory and field settings without ...