- From: Marco Polignano <marco.polignano@uniba.it>
- Date: Thu, 13 Mar 2025 11:13:19 +0100
- To: public-ontolex@w3.org
*** Apologies for cross postings *** *ExUM Workshop @UMAP 2025 - Call For Papers - *** DEADLINE APRIL, 11, 2025 *** ---------------------------------------------------------------------- Workshop on Explainable User Models and Personalised Systems (ExUM@UMAP 2025) co-located with UMAP 2025 (http://www.um.org/umap2025) - 33st ACM Conference on User Modeling, Adaptation and Personalization, June 16-19, 2025 | New York (USA) Twitter: https://x.com/ExUM_Workshop Web: https://swap.di.uniba.it/exum/index.html For any information: marco.polignano@uniba.it, cataldo.musto@uniba.it ================= IMPORTANT DATES ================= * Submission Deadline: April 11, 2025 * Notification: April 28, 2025 * Workshop Papers Camera-ready Submission (TAPS system): May 5, 2025 Please note: All deadlines refer to 11:59 pm AoE (Anywhere on Earth) time. ========= ABSTRACT ========= Adaptive and personalized systems, including Large Language Models (LLMs) have rapidly emerged as transformative technologies, deeply integrated into various aspects of modern life. From conversational agents that provide human-like interactions to recommendation algorithms that curate personalized content such as music, movies, or products, these systems are reshaping how individuals interact with digital platforms. As their influence grows in supporting decision-making, content delivery, and user engagement, it becomes increasingly important to address key issues such as transparency, fairness, and user trust. Frameworks like the EU General Data Protection Regulation (GDPR) and EU AI-Act have highlighted the 'right to explanation,' underscoring the need for users to understand the mechanisms driving these intelligent systems. Despite that, a significant portion of research in these fields has been geared toward maximizing performance, i.e., improving the relevance of the results of personalized systems, often at the expense of explainability. This trade-off risks eroding user trust and poses problems of compliance with ethical and regulatory standards. This initiative aims to create a forum for discussing the pressing challenges, innovative methodologies, and future directions in exploring how transparency, explainability, and user-centric design can be incorporated into these technologies to make them not only effective but also trustworthy, ethical, and aligned with the diverse needs and expectations of their users. ====== TOPICS ====== Topics of interest include but are not limited to: ∑ TRANSPARENT AND EXPLAINABLE PERSONALIZATION STRATEGIES o Scrutable User Models o Transparent User Profiling and Personal Data Extraction o Explainable Personalization and Adaptation Methodologies o Novel strategies (e.g., conversational recommender systems) for building transparent algorithms o Transparent Personalization and Adaptation to Groups of users ∑ TRANSPARENT PERSONALIZATION BASED ON LARGE LANGUAGE MODELS ∑ DESIGNING EXPLANATION ALGORITHMS o Explanation algorithms based on item description and item properties o Explanation algorithms based on user-generated content (e.g., reviews) o Explanation algorithms based on collaborative information o Building explanation algorithms for opaque personalization techniques (e.g., neural networks, matrix factorization, deep learning approaches) o Explanation algorithms based on methods to build group models ∑ DESIGNING TRANSPARENT AND EXPLAINABLE USER INTERFACES o Transparent User Interfaces o Designing Transparent Interaction methodologies o Novel paradigms (e.g. chatbots, LLMs) for building transparent models ∑ EVALUATING TRANSPARENCY AND EXPLAINABILITY o Evaluating Transparency in interaction or personalization o Evaluating Explainability of the algorithms o Designing User Studies for evaluating transparency and explainability o Novel metrics and experimental protocols ∑ OPEN ISSUES IN TRANSPARENT AND EXPLAINABLE USER MODELS AND PERSONALIZED SYSTEMS o Ethical issues (fairness and biases) in user / group models and personalized systems o Privacy management of personal and social data o Discussing Recent Regulations (GDPR) and future directions ============ SUBMISSIONS ============ We encourage the submission of contributions investigating novel methodologies to exploit heterogeneous personal data and approaches to build transparent and scrutable user models. In particular, we accept three kinds of submissions: (A) Regular papers (max. 8 pages + references - double-column ACM format); (B) Short papers (max. 4 pages + references - double-column ACM format); (C) Ongoing projects, Demo, Position and Perspective Papers (max. 2 pages + references - double-column ACM format); Submission site: https://easychair.org/my/conference?conf=umap2025 During the submission process select “ExUM - 7th Workshop on Explainable User Models and Personalised Systems”. All submitted papers will be evaluated by at least two members of the program committee, based on originality, significance, relevance, and technical quality. Note that the references do not count toward page limits. Submissions should be single-blinded, i.e. authors’ names should be included in the submissions. Papers must be formatted according to the new workflow for ACM publications. All accepted papers will be published by ACM as a joint volume of Extended UMAP 2025 Proceedings and will be available via the ACM Digital Library. At least one author of each accepted paper must register for the particular workshop and present the paper there. The templates and instructions are available here: https://authors.acm.org/proceedings/production-information/taps-production-workflow * LaTeX (use \documentclass[manuscript, review]{acmart} in the sample-sigconf-authordraft.tex file for double-column format): https://portalparts.acm.org/hippo/latex_templates/acmart-primary.zip * Overleaf (use \documentclass[manuscript, review]{acmart} in the sample-sigconf-authordraft.tex file for double-column format): https://www.overleaf.com/gallery/tagged/acm-official#.WOuOk2e1taQ * MS Word: https://authors.acm.org/proceedings/production-information/preparing-your-article-with-microsoft-word ============= ORGANIZATION ============= Cataldo Musto - University of Bari, Italy Marco Polignano - University of Bari, Italy Amon Rapp – University of Torino, Italy Giovanni Semeraro - University of Bari, Italy Juergen Ziegler - University of Duisburg Essen ============= PROGRAM COMMITTEE ============= Francesco Barile, Maastricht University Pierpaolo Basile, University of Bari Aldo Moro Veronika Bogina, Tel Aviv University Ludovico Boratto, University of Cagliari Gaetano Dibenedetto, University of Bari Aldo Moro Michael Ekstrand, Drexel University Angelo Geninatti Cossatin, Università degli Studi di Torino Dietmar Jannach, University of Klagenfurt Bart Knijnenburg, Clemson University Arun Balajiee Lekshmi Narayanan, University of Pittsburgh Marco Levantesi, Otto-von-Guericke-Universität Magdeburg Benedikt Loepp, Fraunhofer IMS Noemi Mauro, University of Torino Alessandro Petruzzelli, University of Bari Aldo Moro Mario Alfonso Prado Romero, Gran Sasso Science Institute (GSSI) Erasmo Purificato, Joint Research Centre, European Commission Giuseppe Sansonetti, Roma Tre University Lucia Siciliani, Dipartimento di Informatica - University of Bari Aldo Moro Alain D. Starke, University of Amsterdam Kathrin Wardatzky, University of Zurich
Received on Thursday, 13 March 2025 10:13:57 UTC