Postdoc, Faculty of Electrical Engineering and Computing, University of Zagreb
1 paper at NeurIPS 2025
We use in-context learning as weak supervision to train a student model that internalizes demonstration-induced latent shifts via adapter tuning, enabling efficient inference with improved generalization.
