Multi-Level Explanations for Generative Language Models

arXiv:2403.14459v1 Announce Type: new
Abstract: Perturbation-based explanation methods such as LIME and SHAP are commonly applied to text classification. This work focuses on their extension to generative language models. To address the challenges of text as output and long text inputs, we propose a general framework called MExGen that can be instantiated with different attribution algorithms. To handle text output, we introduce the notion of scalarizers for mapping text to real numbers and investigate multiple possibilities. To handle long inputs, …

abstract arxiv challenges classification cs.ai cs.cl extension framework general generative inputs language language models lime shap text text classification type work