# A New cross-domain strategy based XAI models for fake news detection

arXiv: https://arxiv.org/abs/2302.02122 · HTML: https://mlsanity.com/paper/2302.02122/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 4 references that are in the map.
- First posted on arXiv 4 Feb 2023.

## Abstract (arXiv)

In this study, we presented a four-level cross-domain strategy for fake news detection on pre-trained models. Cross-domain text classification is a task of a model adopting a target domain by using the knowledge of the source domain. Explainability is crucial in understanding the behaviour of these complex models. A fine-tune BERT model is used to. perform cross-domain classification with several experiments using datasets from different domains. Explanatory models like Anchor, ELI5, LIME and SHAP are used to design a novel explainable approach to cross-domain levels. The experimental analysis has given an ideal pair of XAI models on different levels of cross-domain.