Call for Papers

Welcome

We invite submissions for the Explainability and Transparency in AI (XTAI-2026) symposium, part of the UK Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB) Convention. XTAI-2026 seeks to advance research on the rapidly evolving challenges surrounding how, why, and to what extent AI systems can provide meaningful explanations for their outputs. Continuing the mission of XTAI-2022, this symposium examines conceptual, technical, and practical approaches to making automated, data-driven systems more interpretable, trustworthy, and accountable. As AI systems increasingly influence critical decisions in society, understanding their behavior and reasoning has become essential for fostering trust, transparency, and responsible deployment. With AI technologies now deployed at scale, emerging paradigms such as Large Language Models (LLMs), Agentic AI Systems, and Multi-Agent Systems (MAS) illustrate the growing importance of explainability and transparency across contemporary AI. These systems are now widely used in settings where opacity, autonomy, and complex interactions can obscure decision-making processes and outcomes. Their prominence underscores the need for robust explanatory and transparency mechanisms—not as isolated concerns tied to specific architectures, but as foundational requirements for modern AI systems more generally. The symposium aims to bring together scholars and practitioners working on foundational theories, algorithmic techniques, and domain-specific applications of explainability and transparency in AI.

Key themes include, but are not limited to:

• Explainable AI models and algorithms
• Transparency in data processing and decision-making
• Argumentation-based explainability
• Counterfactual Explanation techniques
• Explainability & Transparency for/in:
• Large Language Models (LLMs)
• Agentic AI Systems
• Multi-Agent Systems (MAS)
• Domain-specific Explainability (e.g., finance, healthcare, policy, manufacturing, robotics, education)

XTAI-2026 welcomes contributions from established scholars as well as early-career researchers, exploring approaches that enhance the interpretability, accountability, and trustworthiness of AI systems across diverse domains.

Submission & Publication Details

Submissions must be extended abstracts / full papers and should be sent via Application Portal.

Authors are advised to create their OpenReview profiles well in advance of the submission deadline.

• Profiles created without an institutional email address will undergo a moderation process that may take up to two weeks.
• Profiles created with an institutional email address are activated automatically.

We request that extended abstracts be limited to 2-4 pages and full papers up to 12 pages. Selected papers will be published in the general proceedings of the AISB Convention, with the proviso that at least one author attends the symposium in person to present the paper and participate in general symposium activities.

All extended abstracts and papers accepted for presentation will be offered the opportunity to present a poster in addition to the oral presentation. Submissions deemed unsuitable for oral presentation by the programme committee may be offered a poster presentation only.

Submissions should be in the form of extended abstracts or full papers (with preference to full papers), formatted according to the following template: [MS Word (recent)] [MS Word (older versions)] [LaTeX].

Important Dates

Symposium Organisers

Programme Committee

We look forward to receiving submissions and to welcoming participants to XTAI-2026.