Virgil: Navigating Explainability for Transformer-based Language Models
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Computer Science > Computation and Language
Title: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.
| Comments: | ECML PKDD 2026, Demo Track |
| Subjects: | Computation and Language (cs.CL); Machine Learning (cs.LG) |
| Cite as: | arXiv:2608.25555 [cs.CL] |
| (or arXiv:2608.25555v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.25555
arXiv-issued DOI via DataCite (pending registration)
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