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标题: "Who Uses Open-Weight Models? China and the Shifting Geography of AI in Science"
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## Computer Science > Computers and Society

## Title:Who Uses Open-Weight Models? China and the Shifting Geography of AI in Science

Authors:[Zackary Okun Dunivin](https://arxiv.org/search/cs?searchtype=author&query=Dunivin,+Z+O)

[View PDF](https://arxiv.org/pdf/2608.11090) [HTML (experimental)](https://arxiv.org/html/2608.11090v1)

> Abstract:As LLMs have become a flashpoint for scientific research, computer scientists and STS scholars have advocated the use of open-weight models. Since LLM research has matured and more high-quality model families are available, have researchers adopted open-weight models? We present the first systematic study of model selection in scientific research, analyzing 21 million full-text articles through June 2026 from the Semantic Scholar Open Research Corpus (S2ORC). We employ a mixed NLP pipeline to extract model occurrences in article full text and determine whether they are used or merely mentioned by researchers. We divide our corpus into single- and multi-model family studies, which we take as a proxy for applied and foundational AI research. We find GPT-family models dominate both single- and multi-family research, but that both areas are becoming more diverse over time. In single-family papers, open-weight model use rises steadily, reaching 44.0% in 2026. However, we find that recent growth is driven by the availability of high-quality open-weight Chinese models. Further, a logistic regression model finds that open-weight adoption is heterogeneously distributed, estimating that researchers at Chinese institutions have 2.23 times the odds of using an open-weight model, accounting for 44.0% of the increase in open-weight adoption since 2023. A complementary multinomial model shows this association is concentrated in Chinese open-weight models: in 2026, their adjusted use is 37.1% among papers with Chinese affiliations, a 27.9 percentage-point over papers with no observed China link. These findings suggest that open-weight adoption in science is not a general turn toward open science, but part of a broader realignment of model ecosystems in which platforms and markets, and the sociocultural and geopolitical contexts which shape them, determine which AI systems become scientific instruments.

| Subjects: | Computers and Society (cs.CY) |
| --- | --- |
| Cite as: | [arXiv:2608.11090](https://arxiv.org/abs/2608.11090) \[cs.CY\] |
|  | (or [arXiv:2608.11090v1](https://arxiv.org/abs/2608.11090v1) \[cs.CY\] for this version) |
|  | [https://doi.org/10.48550/arXiv.2608.11090](https://doi.org/10.48550/arXiv.2608.11090) |

## Submission history

From: Zackary Dunivin \[[view email](https://arxiv.org/show-email/58f69265/2608.11090)\]  
**\[v1\]** Tue, 11 Aug 2026 15:57:42 UTC (256 KB)

[Which authors of this paper are endorsers?](https://arxiv.org/auth/show-endorsers/2608.11090) | Disable MathJax ([What is MathJax?](https://info.arxiv.org/help/mathjax.html))
