[CFP] XAI.it 2026: 6th Workshop on Explainable AI, Generative and Agentic Systems: Trust, Transparency, and Human Oversight

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Marco Polignano

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Jun 23, 2026, 5:16:46 AM (6 days ago) Jun 23
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XAI.it 2026

6th Workshop on Explainable AI, Generative and Agentic Systems: Trust, Transparency, and Human Oversight

https://xai-it.github.io/index.html

 

Hosted at 24th International Conference of the Italian Association for Artificial Intelligence - AIxIA 2026, Perugia, Italy, October 6-9, 2026

https://aixia2026.unipg.it/index.html

 

 

### Important Dates ###

Submission deadline: July 20, 2026

Author notification: August 24, 2026

Camera-ready version: September 14, 2026

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Submission Site: https://easychair.org/conferences/?conf=xaiit2026

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Topics of interests include but are not limited to:

- Explainable AI, GenAI and Agentic AI

- Trustable and Transparent AI, GenAI and Agentic Models

- Justification Models in AI, GenAI and Agentic AI

- Interpretable Machine Learning Models

- Strategies to Explain Black Box Decision Systems

- Designing new Explanation Styles and Approaches

- Evaluating Transparency and Interpretability of AI Systems

- Technical Aspects of Algorithms for Explanation

- Theoretical Aspects of Explanation and Interpretability

- Ethics in AI, GenAI and Agentic AI

- Argumentation Theory for Explainable AI, GenAI and Agentic AI

- Natural Language Processing for Explainable AI, GenAI and Agentic AI

- Human-Machine Interaction for Explainable AI, GenAI and Agentic AI

- Fairness and Bias Auditing

- Privacy-Preserving Explanations

- Privacy by Design Approaches for Human Data

- Monitoring and Understanding System Behavior

- Successful Applications of Interpretable AI Systems

- Demo and Proof of Concepts with Explainable Results 

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Explainable AI (XAI) has become a central requirement for deploying modern AI systems, especially agents, LLMs and high‑capacity machine learning models, in safety‑critical, socially sensitive and decision‑support scenarios. Despite their impressive performance, these models are often opaque, making it difficult for users, stakeholders and regulators to understand how outputs are produced, to contest decisions, or to assess potential harms and biases. This opacity undermines trust, slows down real‑world adoption, and creates friction with emerging AI governance frameworks that explicitly call for transparency, accountability, and human oversight.

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We encourage the submission of original contributions, investigating novel methodologies to build transparent and scrutable AI systems and algorithms. In particular, authors can submit:

·      Regular papers (min. 7 pages - max. 12 pages + references - One column CEUR.ws format);

·      Short/Position papers (min. 4 pages - max. 6 pages + references - One column CEUR.ws format format);

The LaTeX template can be downloaded as source file from the CEUR website: http://ceur-ws.org/Vol-XXX/CEURART.zip or accessed as a Template in Overleaf: CEUR.WS Note: All submissions must be compatible with CEUR (https://ceur-ws.org/) and include the CEUR Declaration on Generative AI section (https://ceur-ws.org/GenAI/Policy.html). Papers missing this section will be desk rejected.

 

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All submitted papers will be evaluated by at least two members of the program committee, based on originality, significance, relevance and technical quality. Submissions of full research papers must be in English, in PDF format in the CEUR-WS single-column conference format. Submissions should be single blinded, i.e. authors names should be included in the submissions. Submissions must be made through the EasyChair conference system prior the specified deadline. At least one of the authors should register and take part at the conference in person to make the presentation.


###Proceedings and Post Proceedings###

All accepted papers will be published in the AIxIA series of CEUR-WS.
A selection of the best papers, accepted for the presentation at the workshops, will be invited to submit an extended version for publication on “Intelligenza Artificiale”, the International Journal of the Italian Association for Artificial Intelligence, edited by IOS Press and indexed by Thomson Reuters' "Emerging Sources Citation Index" and Scopus by Elsevier.


###ORGANIZERS###

 

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