[PDG 471] Recursive Language Models

Link to article: https://arxiv.org/pdf/2512.24601
Title: Recursive Language Models
Content: We study LLMs to process arbitrarily long prompts through the lens of inference-time scaling. We propose Recursive Language Models (RLMs), a general inference strategy that treats long prompts as part of an external environment and allows the LLM to programmatically examine, decompose, and recursively call itself over snippets of the prompt. We find that RLMs successfully handle inputs up to two orders of magnitude beyond model context windows and, even for shorter prompts, dramatically outperform the quality of base LLMs while having comparable (or cheaper) cost per query
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