Assess whether rare-event engagement scales to larger language models

Determine whether the interaction between elicitation structure and extreme failure rarity observed in qwen3:8b, llama3.1:8b, and mistral:7b persists, strengthens, or disappears in larger-scale language models.

Background

The study deliberately restricts evaluation to three relatively small open-weight models because local execution makes the rare-event trial schedule computationally feasible and reproducible. This design supports comparisons among the selected models but does not establish how model scale affects the observed interaction between rarity and elicitation structure.

The authors explicitly separate this scaling question from the paper’s primary research objective. Larger models, including models outside the small local open-weight regime, could exhibit the same interaction, a stronger one, or no such interaction at all.

References

Whether the same interaction holds, strengthens, or disappears at larger scale is a real and open question, but it is a different one from what this paper asks, and we do not present these three models as a claim about what happens at scale in either direction.

— Explanatory Engagement Under Rare Anomalous Failure: Asymptotic Rarity in Model Behavior (or: The Asymptotic AI)  (2608.13063 - Mao, 13 Aug 2026) in Section 7.5, On the Choice of Three Small, Open-Weight Models

Improbability did not correlate with judged novelty ($|r|<0.2$, Figure~\ref{fig:prompt}), and a pilot effect ($n=8$) had not replicated. We found no benefit from prompt improbability under the tested operationalizations; whether other operationalizations, developers or judges would find one is open.

— Interrupting the Loop: Periodic Subject Changes Raise Judged Surprise and Connection in Base Language Models  (2608.19893 - Filho, 20 Aug 2026) in Appendix, Section “The prompt”

We further conjecture that the two ends fail for different reasons. Small backbones may be bottlenecked by under-perception of on-stage stimuli, while large backbones may be bottlenecked (also trapped in environment perception but less than small ones) by a built-in resistance to risk-relevant actions such as follow, dm, and join-group, especially under high-risk suspicious cues. In this view, simulating an easily-deceived victim could favor a small backbone shaped by RBHS, where the scaffold plausibly fills the perception gap without inheriting the safety prior that suppresses the very behavior we need to study.

— LiveSim: Simulating Environment-Shaped Users in Multi-Agent Live-Stream Ecosystems  (2608.26849 - Xu et al., 27 Aug 2026) in Section 7, subsection “RBHS Robustness Study”