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#context-engineering

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papersTODAY 04:00 UTC

CLEAR Method Improves LLM Agent Context Through Contrastive Experience Learning

A revised arXiv paper introduces CLEAR, a technique that builds better task context for large language model agents by drawing on prior experience and contrastive learning rather than relying only on retrieval. The approach uses agentic reflection to generate augmented context aimed at improving decision-making. This is a research preprint and results have not been independently verified.

agents/context-engineering/research/llm