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多轮智能体上下文衰退与状态污染基准

📌 One-Sentence Summary 该基准测试评估了各种 AI 模型在 50 次交互步骤中保持准确上下文的能力,结果显示,尽管扁平 RAG 和线性 KV-Cache 模型遭受严重衰退和状态污染,但 XORAS 庞加莱内存系统保持了近乎完美的召回率和零污染。 📝 Summary 该实验测量了多轮智能体对话中的上下文衰退。结果表明,传统方法(扁平 RAG、Gemma-4、Gemini 3.5

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Multi-Turn Agentic Context Decay & State Pollution Benchmark

This benchmark evaluates the ability of various AI models to maintain accurate context over 50 interaction steps, revealing that while flat RAG and linear KV-cache models suffer significant decay and state pollution, the XORAS Poincaré Memory system maintains near-perfect recall and zero pollution.