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arXiv 2609.11365cs.AIcs.LGcs.MA

可移植语义,私有方言:语言模型细胞间潜在通信中的复用与负迁移

Portable Semantics, Private Dialects: Reuse and Negative Transfer in Latent Communication Between Language-Model Cells

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Narcis Marincat

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中文总结 AI 辅助

本研究通过因果审计和适应实验,发现独立训练的语言模型社会间潜在通信接口不共享原始语言,且继承全局接口会严重阻碍后续学习,而重新初始化接口可大幅提升精度。

中文摘要 AI 辅助

在共享基因组的语言模型社会中,受限的证据可见性有利于可复用、价值索引的潜在数据包接口,而父研究中的唯一高性能全局可见模型则学习了一种与情节纠缠的编码。本伴随研究探讨了独立训练的社会是否共享一种数据包语言,在严格零样本迁移失败的情况下,以及继承的接口状态是有助于还是阻碍后续学习。首先,一项受泄漏控制的因果互操作性审计,覆盖六个独立训练的受限社会的全部30个有序对——在密封的保留结构和预注册的原始/正交/线性/非线性对齐阶梯下——表明这六个语义相似的接口并未形成一种原始语言:一对相同初始化的对在双向完全可互操作,第二对呈现不对称的部分兼容性,而所有26个跨初始化方向均未通过任何冻结对齐层级。其次,在测试的分解和单一密封源公式内,源跨度控制将严格零样本失败定位于新操作符指令的解释和执行。第三,在匹配的适应因子设计中,全局训练的通信接口作为严重的负迁移先验:仅重新初始化数据包读取器、写入器和口部,将最终深度三精度从0.169提升至0.857。第四,在两个受限检查点和两个独立冻结的目标流中,继承的接口从未超过预注册的0.10边际的新鲜接口对照。所有主要结论仅限于近迁移的17状态设置;负迁移因子设计涉及一个全局可见的父队列检查点,而附录增加了事后标记的全局孪生案例研究。

英文摘要

In shared-genome language-model societies, restricted evidence visibility favors reusable, value-indexed latent packet interfaces, whereas the sole high-performing globally visible model in the parent study learned an episode-entangled code. This companion study asks whether independently trained societies share one packet language, where strict zero-shot transfer fails, and whether inherited interface state helps or harms later learning. First, a leakage-controlled causal interoperability audit over all 30 ordered pairs of six independently trained restricted societies -- under sealed held-out structure and a preregistered raw/orthogonal/linear/nonlinear alignment ladder -- shows the six semantically similar interfaces do not form one raw language: one same-initialization pair is exactly interoperable in both directions, a second shows asymmetric partial compatibility, and all 26 cross-initialization directions fail every frozen alignment rung. Second, within the tested decomposition and a single sealed source formulation, a source-span control localizes strict zero-shot failure to interpretation and execution of the new operator instructions. Third, in a matched adaptation factorial, the globally trained communication interface acts as a severe negative-transfer prior: reinitializing only the packet reader, writer, and mouth raises final depth-three accuracy from 0.169 to 0.857. Fourth, across two restricted checkpoints and two independently frozen target streams each, inherited interfaces never exceeded fresh-interface controls by the preregistered 0.10 margin. All primary conclusions are bounded to a near-transfer 17-state setting; the negative-transfer factorial concerns one globally visible parent-cohort checkpoint, while an appendix adds a post hoc tagged-global twin case study.

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