Paper-Conference

Overview of PAN 2026: Voight-Kampff Generative AI Detection, Text Watermarking, Multi-author Writing Style Analysis, Generative Plagiarism Detection, and Reasoning Trajectory Detection
For almost two decades now, the PAN lab has been striving to advance the state of the art in text forensics and stylometry through …
Janek Bevendorff, Maik Fröbe, André Greiner-Petter, Andreas Jakoby, Maximilian Mayerl, Preslav Nakov, Henry Plutz, Martin Potthast, Benno Stein, Minh Ngoc Ta, Yuxia Wang, Eva Zangerle
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Beyond Algorithms: A Workshop on the Interdisciplinarity of Recommender Systems (BEYOND 2026)
Recommendation and personalization research is no longer confined to computer science. Relevant questions are actively explored across …
Christine Bauer, Eva Zangerle, Alan Said
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Beyond Top-1: Addressing Inconsistencies in Evaluating Counterfactual Explanations for Recommender Systems (Extended Abstract)
Amir Reza Mohammadi, Andreas Peintner, Michael M. Müller, Eva Zangerle
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Minimal-Perturbation Counterfactuals through Guided Denoising Diffusion for Recommender Systems Explanation
Counterfactual explanations for recommender systems aim to identify minimal changes to a user’s interaction history that would …
Amir Reza Mohammadi, Andreas Peintner, Michael M. Müller, Eva Zangerle
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Can Third-Party Annotators Reliably Evaluate Conversational Recommender Systems?
User-centric evaluation has become a key paradigm for assessing Conversational Recommender Systems (CRS), aiming to capture subjective …
Michael Müller, Amir Reza Mohammadi, Andreas Peintner, Beatriz Barroso Gstrein, Günther Specht, Eva Zangerle
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Overview of PAN 2026: Voight-Kampff Generative AI Detection, Text Watermarking, Multi-author Writing Style Analysis, Generative Plagiarism Detection, and Reasoning Trajectory Detection -- Extended Abstract
Janek Bevendorff, Maik Fröbe, André Greiner-Petter, Andreas Jakoby, Maximilian Mayerl, Preslav Nakov, Henry Plutz, Martin Potthast, Benno Stein, Minh Ngoc Ta, Yuxia Wang, Eva Zangerle
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Overview of PAN 2025: Voight-Kampff Generative AI Detection, Multilingual Text Detoxification, Multi-Author Writing Style Analysis, and Generative Plagiarism Detection
Janek Bevendorff, Daryna Dementieva, Maik Fröbe, Bela Gipp, André Greiner-Petter, Jussi Karlgren, Maximilian Mayerl, Preslav Nakov, Alexander Panchenko, Martin Potthast, Artem Shelmanov, Efstathios Stamatatos, Benno Stein, Yuxia Wang, Matti Wiegmann, Eva Zangerle
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Beyond Algorithms: Reclaiming the Interdisciplinary Roots of Recommender Systems (BEYOND 2025)
This workshop challenges the machine learning-centric focus of modern recommender systems research by reconnecting the field with its …
Eva Zangerle, Alan Said, Christine Bauer
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Beyond Top-1: Addressing Inconsistencies in Evaluating Counterfactual Explanations for Recommender Systems
Explainability in recommender systems (RS) remains a pivotal yet challenging research frontier. Among state-of-the-art techniques, …
Amir Reza Mohammadi, Andreas Peintner, Michael Müller, Eva Zangerle
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Hypergraph-based Temporal Modelling of Repeated Intent for Sequential Recommendation
In sequential recommendation scenarios, user intent is a key driver of consumption behavior. However, consumption intents are usually …
Andreas Peintner, Amir Reza Mohammadi, Michael Müller, Eva Zangerle
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