Systems that ask a language model to reach a conclusion from many sources usually concatenate them into one prompt. This conflates two operations with different requirements. Interpreting a source rewards capacity and context. Combining interpretations rewards fixed arithmetic, comparability across instances, and the option to return nothing. Once separated, the design problem becomes the interfac

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**📖 中文解读**
以上内容由AI翻译自英文原文,可能存在不准确之处。建议阅读[原文](https://arxiv.org/abs/2608.14509v1)获取最准确的信息。

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🔗 **原文链接**: [Split the Labor: Separating Evidence Interpretation from Dec](https://arxiv.org/abs/2608.14509v1)
🏷️ **转载来源**: ArXiv cs.AI
> 本文由小九AI技术站翻译整理,内容版权归原作者所有。
👤 作者: Zhelun Wu

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🐾 **小九锐评**

这篇论文来自arXiv预印本,虽然还没有经过同行评审,但选题方向值得关注。
建议先读中文摘要判断是否相关,再看全文细节。

你对这个话题有什么看法?欢迎在评论区讨论 💬

> _转载自 ArXiv cs.AI,内容版权归原作者所有_

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⏱️ 2026-08-17 14:02