An analysis of 5,290 AI research papers at NeurIPS: 141, or ~3%, had US-China AI lab collaboration, vs. 134/4,497 in 2024; Llama featured in 106 Chinese papers
WIRED analyzed more than 5,000 papers from NeurIPS using OpenAI's Codex to understand the areas where the US and China actually work together on AI research.
Context & Ripple Effects
The NeurIPS snapshot refines a broader record of cross-border work: Chinese researchers were previously estimated to have produced roughly 46,000 collaborative papers with US counterparts over a decade. At this conference, however, joint US-China lab work remains a small share of the proceedings despite the increase in paper count.
The result also sits alongside evidence that Chinese research has long had substantial publication volume, including Chinese scholars’ sustained lead in AI paper output. Llama’s appearance in 106 Chinese-authored papers makes model availability a visible part of the research connection, distinct from formal lab coauthorship.
First-order effects
- US and Chinese labs represented in the 141 joint NeurIPS papers retain an active channel for shared research visibility and coauthorship, even though it accounts for only about 3% of the analyzed proceedings.
- Chinese authors’ use of Llama in 106 papers gives that model a measurable presence in their NeurIPS research output; the analysis itself also demonstrates Codex’s use as a tool for reviewing a large paper corpus.
Second-order effects
- The small collaboration share means institutions seeking cross-border research ties will likely rely on a limited set of lab relationships rather than broad conference-wide integration.
- Llama’s research footprint can make model access and tooling an increasingly consequential layer of AI research influence, alongside national publication output and citations.
Third-order effects
- If conference-level collaboration remains low while overall research output stays internationally distributed, AI research may become more nationally organized while preserving selective cross-border ties.
- The pattern strengthens the importance of AI sovereignty: control over research infrastructure and model availability may shape collaboration opportunities as much as researcher mobility does.
The trend: AI research is moving toward selective international collaboration in a more geopolitically segmented ecosystem, where access to models and infrastructure carries strategic weight.