The work seems to generate per-instance weights that describe the features based on the effect that they have on the outcome. How would you propose to do that with two LLMs?
The questions you raise are very interesting. My question would be, where does the default hyperparameter configuration come from? Additionally, does there exist one hyperparameter configuration that performs well on…
An interesting end-to-end AutoML method
The work seems to generate per-instance weights that describe the features based on the effect that they have on the outcome. How would you propose to do that with two LLMs?
The questions you raise are very interesting. My question would be, where does the default hyperparameter configuration come from? Additionally, does there exist one hyperparameter configuration that performs well on…
An interesting end-to-end AutoML method