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Found 3 papers, 2 papers with code
Labrador: Exploring the Limits of Masked Language Modeling for Laboratory Data
In this work we introduce Labrador, a pre-trained Transformer model for laboratory data.
Conformal Prediction with Large Language Models for Multi-Choice Question Answering
In this work, we explore how conformal prediction can be used to provide uncertainty quantification in language models for the specific task of multiple-choice question-answering.
Towards Reliable Zero Shot Classification in Self-Supervised Models with Conformal Prediction
Self-supervised models trained with a contrastive loss such as CLIP have shown to be very powerful in zero-shot classification settings.
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