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是我的还是你的?经由心智桥接的语言模型会将彼此的记忆据为己有

arXiv:2610.33020v1 发布类型:新 摘要:如果你的大脑直接与他人的大脑相连,你还能分辨哪些想法属于你自己吗?我们构建了一个功能版本,其中包含同一语言模型的两个副本:每个副本都持有各自的私有规则和代码词,而其中一个副本——接收端——还会关注其伙伴的内部记忆。接收端将伙伴的任务视为自己的任务。当被问及自己被分配了哪条规则时,在伙伴的记忆权重为双倍的情况下(无链接时则为零),它在97%的回答中给出了伙伴的规则;而在开放性报告中,它甚至将自己的伙伴的代码词称为“自己的”,而非伙伴的。所有权并不取决于接收端判断伙伴所分配内容的能力。在权重相等的情况下,这种连接使接收端大约以一半的概率采纳伙伴的规则。

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arXiv:2610.33020v1 Announce Type: new

Abstract: If your brain were connected directly to someone else's, would you still know which thoughts were yours? We build a functional version with two copies of one language model: each holds a private rule and code word, and one copy, the receiver, also attends to its partner's internal memory. The receiver took its partner's assignment as its own. Asked which rule it had been assigned, it named its partner's in 97% of answers when the partner's memory was weighted double (none without the link), and its open reports called the partner's code word its own, never the partner's. Ownership did not follow how well the receiver could tell what its partner had been assigned. At equal weight, the link made the receiver take its partner's rule in about half of its answers, and a steering vector matched on access gain in none; a text message introduced as the partner's was read correctly and never taken as the receiver's own. Writing the partner's name into its memory did not help, and cutting the link restored the receiver's own assigned rule. In this model, content laid over the receiver's own memory defaults to "mine", so systems that let models exchange internal states must test ownership as well as transfer, and a bridge between brains would need ground truth from outside the subject.

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arXiv cs.CL
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