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MAD 2025 : Call For Papers: 4th ACM International Workshop on Multimedia AI against Disinformation

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Link: https://www.mad2025.aimultimedialab.ro/
 
When Jun 30, 2025 - Jul 3, 2025
Where Chicago, USA
Submission Deadline Apr 10, 2025
Notification Due Apr 29, 2025
Final Version Due May 5, 2025
Categories    machine learning   deep learning   disinformation   large language models
 

Call For Papers

4th ACM International Workshop on Multimedia AI against Disinformation (MAD’25)
ACM International Conference on Multimedia Retrieval ICMR'25
Chicago, USA, June 30 - July 3, 2025
https://www.mad2025.aimultimedialab.ro/
https://easychair.org/my/conference?conf=mad2025


*** Call for papers ***
************************

* Paper submission due: April 10, 2025
* Acceptance notification: April 29, 2025
* Camera-ready papers due: May 5, 2025
* Workshop @ACM ICMR 2025: June 30, 2025


Modern communication does not rely anymore solely on mainstream media like newspapers or television, but rather takes place over social networks, in real-time, and with live interactions among users. The speedup of distribution and the amount of information available, however, also led to an increased amount of misleading content, disinformation and propaganda. Conversely, the fight against disinformation, in which news agencies and NGOs (among others) take part on a daily basis to avoid the risk of citizens' opinions being distorted, became even more crucial and demanding, especially for what concerns sensitive topics such as politics, health and religion.

Disinformation campaigns are leveraging, among others, AI-based tools for content generation and modification: hyper-realistic visual, speech, textual and video content have emerged under the collective name of "deepfakes", and more recently with the use of Large Language Models (LLMs) and Large Multimodal Models (LMMs), undermining the perceived credibility of media content. It is, therefore, even more crucial to counter these advances by devising new robust and trustworthy AI tools able to detect the presence of inaccurate, synthetic and manipulated content, accessible to journalists and fact-checkers.

Future multimedia disinformation detection research relies on the combination of different modalities and on the adoption of the latest advances of deep learning approaches and architectures. These raise new challenges and questions that need to be addressed to reduce the effects of disinformation campaigns. The workshop, in its fourth edition, welcomes contributions related to different aspects of AI-powered disinformation detection, analysis and mitigation.

Topics of interest include but are not limited to:
- Disinformation detection in multimedia content (e.g., video, audio, texts, images)
- Multimodal verification methods
- Synthetic and manipulated media detection
- Multimedia forensics
- Disinformation spread and effects in social media
- Analysis of disinformation campaigns in societally-sensitive domains
- Robustness of media verification against adversarial attacks and real-world complexities
- Fairness and non-discrimination of disinformation detection in multimedia content
- Explaining disinformation detection results to non-expert users
- Temporal and cultural aspects of disinformation
- Dataset sharing and governance in AI for disinformation
- Datasets for disinformation detection and multimedia verification
- Open resources, e.g., datasets, software tools
- Large Language Models for analyzing and mitigating disinformation campaigns
- Large Multimodal Models for media verification
- Multimedia verification systems and applications
- System fusion, ensembling and late fusion techniques
- Benchmarking and evaluation frameworks


*** Submission guidelines ***
When preparing your submission, please adhere strictly to the ACM ICMR 2025 instructions, to ensure the appropriateness of the reviewing process and inclusion in the ACM Digital Library proceedings. The instructions are available here: https://mad2025.aimultimedialab.ro/submissions/.



*** Organizing committee ***
Dan-Cristian Stanciu (National University of Science and Technology Politehnica Bucharest, Romania)
Roberto Caldelli (CNIT and Mercatorum University, Italy)
Milica Gerhardt (Fraunhofer IDMT, Germany)
Bogdan Ionescu (National University of Science and Technology Politehnica Bucharest, Romania)
Giorgos Kordopatis-Zilos (Czech Technical University in Prague, Czechia)
Symeon Papadopoulos (CERTH-ΙΤΙ, Greece)
Adrian Popescu (CEA LIST, France)
Vera Schmitt (Technical University Berlin, Germany)


The workshop is supported under the following projects: (i) UEFISCDI DeteRel SOL12/2024 Detection of relationships between entities in unstructured and structured data sets (https://deterel.aimultimedialab.ro/), (ii) AI4Debunk (https://ai4debunk.eu/), (iii) vera.ai “VERification Assisted by Artificial Intelligence” (https://www.veraai.eu/), and (iv) News-Polygraph (https://news-polygraph.com/).


On behalf of the organizers,

Cristian Stanciu
https://www.aimultimedialab.ro/

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