arXiv (OAI Expanded)
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CLEAR: Context Augmentation from Contrastive Learning of Experience via Agentic Reflection
Large language model agents rely on effective model context to obtain task-relevant information for decision-making. Many existing context engineering approaches primarily rely on the context generated from the past experience and retrieval mechanisms that reuse these context. However, retrieved con
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