Forecasting Open-Weight AI Model Growth on Hugging Face
As the open-weight AI landscape continues to proliferate-with model
development, significant investment, and user interest-it becomes increasingly
important to predict which models will ultimately drive innovation and shape AI
ecosystems. Building on parallels with citation dynamics in scientific
literature, we propose a framework to quantify how an open-weight model's
influence evolves. Specifically, we adapt the model introduced by Wang et al.
for scientific citations, using three key parameters-immediacy, longevity, and
relative fitness-to track the cumulative number of fine-tuned models of an
open-weight model. Our findings reveal that this citation-style approach can
effectively capture the diverse trajectories of open-weight model adoption,
with most models fitting well and outliers indicating unique patterns or abrupt
jumps in usage.
67bd46ea3e090b402d70f1f4
Kushal Raj Bhandari
extracted_confirmed
2025-02-25T04:30:32.676Z
64dfbcb18e2084e1d7b51b46
/avatars/fafe30beea2d7e8eec3f3ba985c582f7.svg
Kushal Raj Bhandari
user
KBhandari11
67bd46ea3e090b402d70f1f5
Pin-Yu Chen
admin_assigned
2025-02-25T16:34:05.126Z
6495dd0b71f6708e0f990032
https://cdn-avatars.huggingface.co/v1/production/uploads/6495dd0b71f6708e0f990032/PBIjdKNnpkxvR_3djCGVm.png
Pin-Yu Chen
user
pinyuchen
67bd46ea3e090b402d70f1f6
Jianxi Gao
Forecasting Open-Weight AI Model Growth on Hugging Face
As the open-weight AI landscape continues to proliferate-with model
development, significant investment, and user interest-it becomes increasingly
important to predict which models will ultimately drive innovation and shape AI
ecosystems. Building on parallels with citation dynamics in scientific
literature, we propose a framework to quantify how an open-weight model's
influence evolves. Specifically, we adapt the model introduced by Wang et al.
for scientific citations, using three key parameters-immediacy, longevity, and
relative fitness-to track the cumulative number of fine-tuned models of an
open-weight model. Our findings reveal that this citation-style approach can
effectively capture the diverse trajectories of open-weight model adoption,
with most models fitting well and outliers indicating unique patterns or abrupt
jumps in usage.
A framework based on citation dynamics tracks and predicts the influence and adoption of open-weight models through parameters of immediacy, longevity, and relative fitness.
citation dynamics fine-tuned models immediacy longevity relative fitness