奠基效应塑造了开放大语言模型家族中多模态的进化动态
Founder effects shape the evolutionary dynamics of multimodality in open LLM families
AI总结：
研究通过分析模型谱系数据，发现多模态能力在开放大语言模型家族中通过罕见的奠基事件进入，并在后代谱系中快速扩展，导致多模态能力的采用动态呈现突变特征。
摘要：
大型语言模型（LLM）家族正在迅速改进，但尚不清楚多模态能力如何在开放家族中迅速出现和传播。利用ModelBiome AI生态系统数据集中的Hugging Face模型元数据和记录的谱系字段（>1.8×10^6个模型条目），我们量化了多模态能力随时间的变化以及在记录的父-子关系中的分布。跨模态任务在更广泛的生态系统中在成为主要开放LLM家族常见之前就已广泛存在：在这些家族中，多模态能力在2023年和2024年大部分时间仍罕见，然后在2024-2025年急剧增加，并被图像-文本视觉-语言任务主导。在主要家族中，第一个视觉-语言模型（VLM）变体通常在文本生成发布后数月出现，延迟范围从约1个月（Gemma）到某些家族超过一年，甚至GLM为26个月。谱系条件的转移率显示弱的跨类型转移：在文本生成父模型的微调边中，只有0.218%产生VLM后代。相反，多模态能力主要在现有VLM谱系内扩展：94.5%的VLM-子微调边来自VLM父模型，而非文本生成父模型的4.7%。在模型层面，大多数VLM发布作为无记录父模型的新根（~60%），其余主要源自VLM衍生；创始人集中分析显示谱系内快速放大后多样化。这些结果表明，多模态能力通过罕见的创始人事件进入开放LLM家族，然后在后代谱系中快速扩展，产生突变的采用动态，可能诱导多模态能力的转移限制扩展行为。
英文摘要：
Large language model (LLM) families are improving rapidly, yet it remains unclear how quickly multimodal capabilities emerge and propagate within open families. Using the ModelBiome AI Ecosystem dataset of Hugging Face model metadata and recorded lineage fields (>1.8x10^6 model entries), we quantify multimodality over time and along recorded parent-to-child relations. Cross-modal tasks are widespread in the broader ecosystem well before they become common within major open LLM families: within these families, multimodality remains rare through 2023 and most of 2024, then increases sharply in 2024-2025 and is dominated by image-text vision-language tasks. Across major families, the first vision-language model (VLM) variants typically appear months after the first text-generation releases, with lags ranging from ~1 month (Gemma) to more than a year for several families and ~26 months for GLM. Lineage-conditioned transition rates show weak cross-type transfer: among fine-tuning edges from text-generation parents, only 0.218% yield VLM descendants. Instead, multimodality expands primarily within existing VLM lineages: 94.5% of VLM-child fine-tuning edges originate from VLM parents, versus 4.7% from text-generation parents. At the model level, most VLM releases appear as new roots without recorded parents (~60%), while the remainder are predominantly VLM-derived; founder concentration analyses indicate rapid within-lineage amplification followed by diversification. Together, these results show that multimodality enters open LLM families through rare founder events and then expands rapidly within their descendant lineages, producing punctuated adoption dynamics that likely induce distinct, transfer-limited scaling behavior for multimodal capabilities.
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