2nd CfP - DaQuaMRec 2026: 2nd International Workshop on Data Quality-Aware Multimodal Recommendation
Claudio Pomo
**Apologies for cross-posting**
DaQuaMRec: 2nd International Workshop on Data Quality-Aware Multimodal Recommendation
Held in conjunction with the 20th ACM Conference on Recommender Systems (RecSys 2026)
Full details are available online: https://sites.google.com/view/daquamrec2026/
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MOTIVATION AND GOALS
Multimodal recommender systems are transforming the way we experience digital services, enabling smarter and richer recommendations in domains such as fashion, music, food, e-commerce, and digital media. By combining data from images, text, audio, video, and other heterogeneous signals, these systems can support richer user profiling and more accurate recommendations than traditional single-modality approaches.
However, multimodal recommender systems are highly sensitive to the quality of the data they rely on. Noisy inputs, missing modalities, duplicated or weakly supervised data, misaligned information across modalities, and embedded biases can significantly affect system performance, robustness, explainability, and fairness.
DaQuaMRec, the 2nd International Workshop on Data Quality-Aware Multimodal Recommendation, brings this foundational concern to the forefront. The workshop offers a dedicated venue to discuss how data quality shapes multimodal recommendation pipelines, from data collection and preprocessing to modeling, evaluation, and deployment. Its goal is to foster focused discussions and catalyze new research on understanding, evaluating, and improving data quality in multimodal recommendation settings.
IMPORTANT DATES
Call for Papers publication: April 21, 2026
Paper submission deadline: July 20, 2026
Reviewer deadline: August 7, 2026
Author notification: August 14, 2026
Camera-ready version deadline: August 28, 2026
Workshop date: September 28, 2026
All deadlines are 11:59 PM AoE.
TOPICS OF INTEREST
Topics of interest include, but are not limited to:
Noisy multi-modal data
Incomplete or missing multimodal data
Bias in multimodal data
Preference misalignment across modalities
Fairness issues in multimodal recommendation
Assessing multimodal data quality in recommendation
CONTRIBUTION FORMATS
DaQuaMRec welcomes submissions in the following categories:
Research Papers:
Long papers, up to 8 pages excluding references, should present original work that makes a clear and novel contribution and is positioned with respect to the state of the art.
Short papers, up to 4 pages excluding references, may present early-stage research, promising ideas, negative results, or thought-provoking perspectives that can stimulate discussion and future work.
Reproducibility and Resource Papers:
Long papers, up to 8 pages excluding references, should present substantial contributions such as comprehensive tools, large-scale datasets, benchmarks, or in-depth reproducibility analyses.
Short papers, up to 4 pages excluding references, may describe smaller-scale resources, focused tool descriptions, or preliminary reproducibility efforts of interest to the community.
Position Papers:
Position papers, up to 2 pages excluding references, are intended for short, critical, or visionary contributions that highlight future directions, emerging challenges, or reflective perspectives on the field. They should aim to spark discussion and inspire future research, even in the absence of experimental results.
SUBMISSION AND PUBLICATION
Submissions are open.
Submit your paper through EasyChair at:
https://easychair.org/my/conference?conf=recsys2026workshops
Please make sure to select:
Second International Workshop on Data Quality-Aware Multimodal Recommendation
All submissions must be written in English, submitted as PDF files, and formatted using the CEUR-WS single-column conference format.
All submissions will undergo a double-blind peer review process. Review criteria include relevance to the workshop, originality, significance of the contribution, technical soundness, clarity of presentation, quality of references, and reproducibility.
Authors are encouraged to share code and supplementary material through an anonymous repository to support reproducibility. Submissions that are not properly anonymized, do not follow the required formatting, or disregard the submission guidelines may be rejected without review.
Accepted long and short papers will be published in the CEUR Workshop Proceedings and presented in the main workshop program. Position papers will also be included in the proceedings, and a selection of them may be invited for oral presentation.
At least one author of each accepted paper must register for and attend the workshop in order to present the work.
ORGANIZING COMMITTEE
Claudio Pomo - Politecnico di Bari, Italy
Daniele Malitesta - Université Paris-Saclay, France
Alberto Carlo Maria Mancino - Politecnico di Bari, Italy
Marta Moscati - JKU Linz and Albatross AI, Austria
Dietmar Jannach - University of Klagenfurt, Austria
Yubin Kim - Vody, Inc., USA
Aixin Sun - NTU Singapore, Singapore
CONTACT US
For any questions or inquiries, please contact us at: