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实体 Language Is an Insufficient Substrate for Quantitative Reasoning, and Consequential Domains Need Large Quantitative Models

Language Is an Insufficient Substrate for Quantitative Reasoning, and Consequential Domains Need Large Quantitative Models

PulseAugur coverage of Language Is an Insufficient Substrate for Quantitative Reasoning, and Consequential Domains Need Large Quantitative Models — every cluster mentioning Language Is an Insufficient Substrate for Quantitative Reasoning, and Consequential Domains Need Large Quantitative Models across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_252131 ·

    新论文提出用大型量化模型取代LLM处理关键任务

    一篇新论文认为，当前的大型语言模型（LLMs）在关键的量化决策任务上存在根本性不足。作者们提出，基于人类文本训练的语言模型的描述性本质，会固有地丢失关键的量化信息。他们引入了大型量化模型（LQMs）的概念，该模型设计时具备从输出追溯到源数据的可复现性和 lineage 等特定属性，并认为这些属性对于金融定价、患者分诊和网络安全等领域是必需的。