Here you present the link between two models using the fact that their centroïd token are the same. Do you know any other similar correlation of this type? Maybe by finding other links between a model an its former models you could gather them and have a more reliable tool to predict if Model A and Model B share a past training.
In particular, I found that there seems to be a correlation between the size of a model and the best prompt for better accuracy [https://arxiv.org/abs/2105.11447 , figure5]. The link here is only the size of the models, but I thought that the size was a weird explanation, and so thought about your article.
Here you present the link between two models using the fact that their centroïd token are the same.
Do you know any other similar correlation of this type? Maybe by finding other links between a model an its former models you could gather them and have a more reliable tool to predict if Model A and Model B share a past training.
In particular, I found that there seems to be a correlation between the size of a model and the best prompt for better accuracy [https://arxiv.org/abs/2105.11447 , figure5]. The link here is only the size of the models, but I thought that the size was a weird explanation, and so thought about your article.
Hope this may somehow help :)