Polarity-Aware Probing for Quantifying Latent Alignment in Language Models

This article, sourced from ArXiv, likely presents a novel method for evaluating the alignment of language models. The title suggests a focus on understanding how well a model's internal representations (latent space) reflect desired properties or behaviors, using a technique called "polarity-aware probing." This implies the research aims to quantify the degree to which a model's internal workings align with specific goals or biases, potentially related to sentiment or other polarities.