[AIXIA][CFP] ACM TOMM, Special Issue on "Towards Responsible and Explainable Multi-Modal Fusion"

[Lucia CASCONE]

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*** Call for Papers - ACM Transactions on Multimedia Computing, Communications, and Applications ***

Special Issue on Towards Responsible and Explainable Multi-Modal Fusion

PAPER SUBMISSION DEADLINE: August 31, 2026

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OVERVIEW

Multi-modal fusion, defined as the integration of heterogeneous data sources such as text, images, audio, sensor streams, and structured records, has become a cornerstone of modern artificial intelligence with applications across healthcare, autonomous systems, social computing, and multimedia analysis. By combining complementary information from different modalities, fusion techniques enhance contextual understanding, robustness, and predictive performance. As these systems grow in complexity and are increasingly adopted in high-stakes scenarios, it becomes essential to embed responsibility, transparency, and fairness as intrinsic requirements in both design and evaluation.
 
This Special Issue aims to consolidate emerging contributions that embed explainability, interpretability, and ethical principles directly into the architecture, training, and evaluation of multi-modal systems. We particularly encourage submissions addressing high-impact domains such as healthcare, autonomous systems, and social computing, where trustworthy AI is critical.

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SPECIAL ISSUE TOPICS

Topics include but are not limited to:

•  Responsible and explainable multi-modal fusion architectures and evaluation protocols 
• Integration and alignment of foundation models and multi-modal large language models for interpretable decision-making. 
• Generative and synthetic data for responsible and robust multi-modal fusion. 
• Bias detection and mitigation, fairness assessment, and accountability in multi-modal systems. 
• Transfer learning and domain adaptation for adaptive and trustworthy multi-modal fusion. 
• Adversarial robustness and security in cross-modal environments. 
• Continual and lifelong learning in evolving multi-modal settings. 
• Federated, edge, and privacy-preserving multi-modal learning frameworks.  

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IMPORTANT DATES

• Submission deadline: August 31, 2026
• First-round review decisions: October 31, 2026
• Deadline for revised submissions: December 15, 2026
• Notification of final decisions: February 15, 2027
• Tentative publication: April 2027

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GUEST EDITORS

• Lucia Cascone - University of Salerno, Italy (lcas...@unisa.it)
• Emanuela Marasco - Virginia Commonwealth University, USA (mara...@vcu.edu)
• Imad Rida - Université de Technologie de Compiègne, France (imad...@utc.fr)

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SUBMISSION AND REVIEW DETAILS

Prospective authors are invited to submit their manuscripts electronically in accordance with the ACM TOMM author guidelines (https://tomm.acm.org/authors.cfm). Manuscripts that do not comply with these guidelines will not be considered. Submissions must fall within the scope of ACM TOMM.

Please submit your papers through the online system (https://mc.manuscriptcentral.com/tomm) and ensure that you select the appropriate Special Issue during submission. Manuscripts must not be previously published or under review elsewhere.

For questions or further information, please contact:
Lucia Cascone (lcas...@unisa.it)