Agents & Tool Use · 2025
Recursive Language Models
Proposed treating long prompts as external environment that LLMs programmatically examine and recursively call themselves over, enabling processing of inputs orders of magnitude beyond context window limits.
Editorial record
Plain-language summary
Recursive Language Models treat the user prompt as a variable in a REPL environment rather than feeding it directly into the neural network. The LLM writes code to peek into and decompose the prompt, and iteratively invokes itself recursively over programmatic snippets. This paradigm processes inputs more than 10x beyond context limits while dramatically outperforming vanilla frontier LLMs and common long-context scaffolds, maintaining strong performance even at 10M+ token scale with comparable cost.
Source record
Provenance
- Record ID
- P-665
- Record created
- 2026-08-12
- Last reviewed
- 2026-08-12
- Record version
- 1
- https://arxiv.org/abs/2512.24601
- arXiv:2512.24601
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