3 papers
cs.CL2026
Learned Readout Tokens for Extracting Large Language Model Confidence
Nima Seifi, Martin Ester
Large language models (LLMs) are increasingly used within everyday applications where their responses have significant downstream impacts. For responsible deployment of such system…
cs.CV2026
PAS: Estimating the target accuracy before domain adaptation
Raphaella Diniz, Jackson de Faria, Martin Ester
The goal of domain adaptation is to make predictions for unlabeled samples from a target domain with the help of labeled samples from a different but related source domain. The per…
cs.LG2024
Improving OOD Generalization of Pre-trained Encoders via Aligned Embedding-Space Ensembles
Shuman Peng, Arash Khoeini, Sharan Vaswani +1
The quality of self-supervised pre-trained embeddings on out-of-distribution (OOD) data is poor without fine-tuning. A straightforward and simple approach to improving the generali…