A translation between models doesn't seem possible because there are actually no "common dimensions" at all between models. That is, each dimension has a completely different semantic meaning, in different models, but also it's the combination of dimension values that begin to impart real "meaning".
For example, the number of different unit vector combinations in a 1500 dimensional space is like the number of different ways of "ordering" the components, which is 5^4114
.
EDIT: And the point of that factorial is that even if the dimensions were "identical" across two different LLMs but merely "scrambled" (in ordering) there would be that large number to contend with to "unscramble".
For example, the number of different unit vector combinations in a 1500 dimensional space is like the number of different ways of "ordering" the components, which is 5^4114 .
EDIT: And the point of that factorial is that even if the dimensions were "identical" across two different LLMs but merely "scrambled" (in ordering) there would be that large number to contend with to "unscramble".