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English(EN) Towards Foundation Decision Models: Drex

Drex决策模型提供更快、更一致的AI输出

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员推出Drex，这是一系列四种新的开源决策模型，旨在与传统的自回归大型语言模型相比，提供更一致、更高效的输出。这些模型拥有80亿至350亿参数，通过单次前向传播处理请求，无需自回归解码，显著降低了延迟。Drex模型在Decision Index 0.4.1和Decision Bench v4等基准测试中取得了最先进的性能，其中'Max'变体在速度上远超GPT-6 Sol和Claude Opus 5.5等模型，同时表现出具有竞争力的结果。 AI

影响 这些模型为自回归LLM提供了一种更快、更一致的替代方案，有望改进生产AI应用。

排序理由 该集群描述了一个新的开源AI模型系列的发布及其在基准测试上的表现，符合研究类别。

在 arXiv cs.CL 阅读 →

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Drex决策模型提供更快、更一致的AI输出

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该集群描述了一个新的开源AI模型系列的发布及其在基准测试上的表现，符合研究类别。
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Nischay Dhankhar, Alisher Amantay, Zhanibek Datbayev, Darkhan Akhmetov, Yash Shah, Nurmukhamed Ubaidullayev, Raman Saparkhan, Dos Baha, Abulhair Saparov ·

    迈向基础决策模型：Drex

    arXiv:2611.07854v1 Announce Type: new Abstract: Autoregressive approaches with large language models, such as long chain-of-thought reasoning, have become the default for new AI applications because they reach higher accuracy on a wide range of tasks. In production, however, they…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    迈向基础决策模型：Drex

    Drex open decision models return probability distributions over user-supplied options without autoregressive decoding, using supervised fine-tuning, RLAF, and consistency losses to improve accuracy, robustness, and latency.

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