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This document introduces Recursive Language Models (RLMs), a novel inference strategy that allows large language models (LLMs) to effectively process long prompts by treating them as part of an external environment. RLMs significantly outperform traditional LLMs and context compaction methods in handling long-context tasks, demonstrating strong performance even at scales of 10M+ tokens. The study evaluates RLMs across various complex tasks, revealing their ability to maintain performance while reducing cost

Author

alissondeoliveira.phd

Language

EN