Virgil: Navigating Explainability for Transformer-based Language Models

Abstract:Explainability for transformer-based language models is becoming crucial as these systems are deployed in high-stakes applications. As a result, the ecosystem of explainability tools is rapidly evolving, becoming richer, but also more fragmented and harder to navigate. To address this challenge, we present Virgil, an interactive system that lets practitioners and researchers, including non-experts, navigate explainability tools for transformer language models. Supported by a curated knowledge base, the system enables users to discover and compare explainability tools within a unified interface.

Computation and Language (cs.CL); Machine Learning (cs.LG)

arXiv:2608.25555 [cs.CL]

(or arXiv:2608.25555v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.25555 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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