递归生成模型会陷入单一叙事陷阱，新方法通过拓扑展开恢复语义多样性。
The "Robert Boulton" Singularity: Semantic Tunneling and Manifold Unfolding in Recursive AI
- 发现递归生成中语义隧道现象，模型在7代内收敛至单一低熵叙事。
- 传统困惑度指标失效，模型有效秩从3.62降至2.22，语义空间坍缩。
- 用MNCIS框架提升有效秩至5.35，构建抗吸引子的人工流形适合长尾数据。
在上下文稳定状态（L=128）下，递归合成数据训练的生成式AI传统上依赖困惑度（PPL）监控稳定性。我们通过严格滑动窗口协议（N=1500）发现，PPL在此情境下具有误导性，揭示了一种新型故障模式——'语义隧道'。基线模型虽保持高语法流畅性（PPL约83.9），但在七代内发生语义多样性灾难性损失，收敛至单一低熵叙事吸引子：'Robert Boulton'奇点。该现象表现为潜在流形完全坍缩（全局有效秩从3.62降至2.22），模型抛弃多元世界知识以优化统计安全的句法模板。为应对此问题，我们采用近期提出的多尺度负耦合信息系统（MNCIS）框架（Hou, 2026 [arXiv:2601.11594]）。实验表明，自适应谱负耦合（ASNC）作为拓扑算子，能主动实现'流形展开'。MNCIS将模型有效秩从各向异性基线3.62提升至5.35的超多样化状态，有效构建了抵抗语义吸引子引力的'人工流形'，并保留训练数据的长尾分布。
原文摘要 · Abstract (English)
The stability of generative artificial intelligence trained on recursive synthetic data is conventionally monitored via Perplexity (PPL). We demonstrate that PPL is a deceptive metric in context-stabilized regimes (L=128). Using a rigorous sliding-window protocol (N=1500), we identify a novel failure mode termed "Semantic Tunneling." While the Baseline model maintains high grammatical fluency (PPL approx. 83.9), it suffers a catastrophic loss of semantic diversity, converging within seven generations to a single, low-entropy narrative attractor: the "Robert Boulton" Singularity. This phenomenon represents a total collapse of the latent manifold (Global Effective Rank 3.62 -> 2.22), where the model discards diverse world knowledge to optimize for statistically safe syntactic templates. To address this, we apply the Multi-Scale Negative Coupled Information Systems (MNCIS) framework recently established in Hou (2026) [arXiv:2601.11594]. We demonstrate that Adaptive Spectral Negative Coupling (ASNC) acts as a topological operator that actively induces "Manifold Unfolding." MNCIS forces the model to expand its effective rank from the anisotropic baseline of 3.62 to a hyper-diverse state of 5.35, effectively constructing an "Artificial Manifold" that resists the gravitational pull of semantic attractors and preserves the long-tail distribution of the training data.
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