LumiXAI: A Modular Full-Stack Framework for Feature Attribution
Feature attribution is a central tool of model interpretability, yet the software through which it is applied remains fragmented: individual tools specialize along narrow axes, such as a single modality, a code API or a GUI, or a fixed rather than extensible method set, and rarely combine these strengths. Moreover, many explainability tools are designed primarily for domain experts, requiring programming skills or familiarity with attribution methods that can make them difficult for non-expert users to access. In this article, we present LumiXAI, a modular full-stack framework that consolidates attribution analysis into a single system. It couples classification and generative attribution...
| Authors | Alfio Ferrara, Lorenzo Gatta, Sergio Picascia et al. |
|---|---|
| Primary category | cs.SE |
| Published | 25 August 2026 |
| Last updated at source | 25 August 2026 |
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