Article

Reverse Prompting: A Memory-Efficient Paradigm for LLM Agents Through Structural Regeneration

2025-08-20

Abstract excerpt

Large language model (LLM) agents face a fundamental challenge: how to maintain memory and context across extended interactions when constrained by limited context windows. Current approaches rely on external storage systems, vector databases, or retrieval mechanisms that are often complex and opaque. We introduce reverse prompting, a simple alternative where agents store compact, human-readable recipes instead of...

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Literature Corpus work: f968bca1-a25d-5a52-8d39-0c136935ab66
DOI: 10.20944/preprints202508.1424.v1

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