R-KV

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    "@id": "https://agentsignals.ai/agents/r-kv",
    "name": "R-KV",
    "description": "R-KV is a technology published at NeurIPS 2025, aimed at optimizing the performance of inference models through a redundancy-aware cache compression method. This technology improves model inference efficiency and cache utilization by reducing redundant data in the cache, making it particularly suitable for large-scale language models and other deep learning application scenarios.",
    "url": "https://agentsignals.ai/agents/r-kv",
    "applicationCategory": "研究",
    "operatingSystem": "GitHub",
    "sameAs": "https://github.com/Zefan-Cai/R-KV",
    "installUrl": "https://github.com/Zefan-Cai/R-KV",
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    "featureList": [
      "Redundancy-aware cache compression",
      "Improve inference efficiency",
      "Suitable for large language models"
    ],
    "datePublished": "2025-12-05T17:17:06.183204+00:00",
    "dateModified": "2025-12-19T05:06:57.825415+00:00",
    "publisher": {
      "@type": "Organization",
      "name": "Agent Signals",
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      {
        "@type": "Question",
        "name": "What is R-KV?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "R-KV is a redundancy-aware cache compression technique designed for inference models."
        }
      },
      {
        "@type": "Question",
        "name": "What features does R-KV offer?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "Redundancy-aware cache compression, Improve inference efficiency, Suitable for large language models"
        }
      },
      {
        "@type": "Question",
        "name": "What are the use cases for R-KV?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "Large-scale language model inference optimization, Deep learning model deployment, Model acceleration in cloud services"
        }
      },
      {
        "@type": "Question",
        "name": "What are the advantages of R-KV?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "显著提升缓存利用率, 降低模型推理成本, 易于集成到现有系统"
        }
      },
      {
        "@type": "Question",
        "name": "What are the limitations of R-KV?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "可能需要额外的配置和优化, 对特定模型效果可能有限"
        }
      }
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