The Use of Open Models in Research | Center for Security and Emerging Technology

"There is widespread consensus that open and freely available AI models benefit research. Yet there is a lack of empirical evidence detailing how this relationship manifests. This report aims to fill this gap by investigating the use of open large language models (LLMs) in published research, overviewing what organizations and countries use them most frequently, and considering their wider impact on research. To this end, we identify and analyze more than 250 publications that use open models in ways that require access to model weights, and derive a taxonomy of use cases that openly available model weights exclusively or predominantly enable. We then review more than 130 publications that use closed models to compare use cases when model weights are and are not openly available. Our analysis finds that open models enable a more diverse range of use cases than closed models. Of the eight high-level use cases for AI models we identified, five are exclusively enabled by access to model weights, two predominantly require weights, and one does not require weights. Those requiring weights include continuously pretraining models to expand their general knowledge, compressing models to improve their efficiency, combining different models or synchronizing their modalities (e.g., text and imagery), and measuring the functionality of models on hardware or the performance of hardware when running models."