Das L3S ist ein Forschungszentrum für grundlagen- und anwendungsorientierte Forschung im Bereich Digitale Transformation sowie Data- und Web-Science. L3S-Forscher entwickeln zukunftsweisende Methoden und Informationstechnologien für intelligente, zuverlässige und verantwortungsvolle Systeme, welche zur Gestaltung der digitalen Transformation und zur nachhaltigen Innovation beitragen. Der Wissentransfer in Wirtschaft, Politik und Gesellschaft bildet einen zentralen Baustein der Aktivitäten des L3S.

Das L3S erforscht die Auswirkungen des digitalen Wandels, um aus den Erkenntnissen Handlungsoptionen, -empfehlungen sowie Innovationsstrategien für die Wirtschaft, die Politik und Gesellschaft herzuleiten. Durch Forschung, Entwicklung und Beratung trägt das L3S gemeinsam mit seinen Partnern zur digitalen Transformation insbesondere in den Bereichen Mobilität, Gesundheit, Produktion und Bildung bei.

Das L3S ist eine gemeinsame Einrichtung der Leibniz Universität Hannover und der Technischen Universität Braunschweig mit rund 150 Wissenschaftlern aus unterschiedlichen Disziplinen an Universitäten und einem Leibniz-Institut (der TIB). Das aktuelle jährliche Drittmittelvolumen des L3S beträgt etwa 6 Mio. Euro, Niedersachsen fördert das L3S zusätzlich mit jährlich etwa 2 Mio. Euro. Das L3S wurde 2011 und 2014 vom Wissenschaftsrat als exzellente Einrichtung evaluiert, führend im Bereich Web Science.

• Beyond Understanding: The under-Explored Role of Affect in Student-AI Interactions. Klumbytė, Goda; Stöter, Lea; Lackner, Konstantin; Horn, Viktoria; Uhlmann, Markus; Knoth, Nils; Bläsing, Lisa Marie; Draude, Claude R. M. Davison, H. Tellioglu (eds.) (2027). 135–152.

  This paper presents findings of a small-scale qualitative interview study of students' use of generative AI tools in their study practices at a German University, and the affective dimensions that emerged in AI understanding and use. We report how affective dimensions manifested through various sites of “(gut) feelings” in AI evaluation and verification as well as in AI use practices, constituting three types of affect-as-resource, namely epistemic resource, access and emotional scaffolding, and affect as interaction resource. We argue that, beyond understanding how individual affective states of the user might affect generative AI understanding and use practices, it is important to critically address affect as a relational domain of agency.
• Beyond Understanding: The under-Explored Role of Affect in Student-AI Interactions. Klumbytė, Goda; Stöter, Lea; Lackner, Konstantin; Horn, Viktoria; Uhlmann, Markus; Knoth, Nils; Bläsing, Lisa Marie; Draude, Claude R. M. Davison, H. Tellioglu (eds.) (2027). 135–152.

  This paper presents findings of a small-scale qualitative interview study of students' use of generative AI tools in their study practices at a German University, and the affective dimensions that emerged in AI understanding and use. We report how affective dimensions manifested through various sites of “(gut) feelings” in AI evaluation and verification as well as in AI use practices, constituting three types of affect-as-resource, namely epistemic resource, access and emotional scaffolding, and affect as interaction resource. We argue that, beyond understanding how individual affective states of the user might affect generative AI understanding and use practices, it is important to critically address affect as a relational domain of agency.
• Beyond Understanding: The under-Explored Role of Affect in Student-AI Interactions. Klumbytė, Goda; Stöter, Lea; Lackner, Konstantin; Horn, Viktoria; Uhlmann, Markus; Knoth, Nils; Bläsing, Lisa Marie; Draude, Claude R. M. Davison, H. Tellioglu (eds.) (2027). 135–152.

  This paper presents findings of a small-scale qualitative interview study of students' use of generative AI tools in their study practices at a German University, and the affective dimensions that emerged in AI understanding and use. We report how affective dimensions manifested through various sites of “(gut) feelings” in AI evaluation and verification as well as in AI use practices, constituting three types of affect-as-resource, namely epistemic resource, access and emotional scaffolding, and affect as interaction resource. We argue that, beyond understanding how individual affective states of the user might affect generative AI understanding and use practices, it is important to critically address affect as a relational domain of agency.
• Unlawful by design: Exposing the human rights costs of generative AI. Technical Report (POL 40/0996/2026), International, Amnesty (2026).

  This briefing examines how standalone generative AI systems, based on unlawful web scraping, are in conflict with international human rights law (IHRL) and standards through their design, development and deployment. While these technologies promise sophisticated automation and efficiency, they rely on data collection and model training practices that abuse privacy rights, enable discrimination, and threaten freedom of expression and thought. Amnesty International finds that standalone generative AI systems, based on unlawful web scraping, depend on mass invasions of privacy by design, and are fundamentally incompatible with IHRL. As such, Amnesty International is calling for a prohibition of such systems.
• UP2DATE: Shared Task on Systematic Review Updates. Achkar, Pierre; Gollub, Tim; Potthast, Martin; Eickhoff, Carsten; Scells, Harrisen in CEUR Workshop Proceedings, I. Frommholz, C. K. Kreutz, P. Mayr, G. Cabanac (eds.) (2026). (Vol. 4187) 78–83.
• A Large-Scale, Cross-Disciplinary Corpus of Systematic Reviews. Achkar, Pierre; Gollub, Tim; Simons, Arno; Scells, Harrisen; Potthast, Martin (2026). abs/2604.22864
• Trigger Warnings are Grounded in a Shared Vocabulary: A Corpus Analysis with User-Generated Labels. Heineking, Sebastian; Wiegmann, Matti; Wolska, Magdalena; Stein, Benno; Potthast, Martin S. Piperidis, N. Bel, H. van den Heuvel, N. Ide, S. Krek, A. Toral (eds.) (2026). 7106–7125.
• Retrieval-Augmented Generation -- The Future of Search? (Dagstuhl Seminar 25391). Hagen, Matthias; Mothe, Josiane; Muresan, Smaranda; Potthast, Martin; Zhang, Min; Stein, Benno; Heineking, Sebastian (M. Hagen; J. Mothe; S. Muresan; M. Potthast; M. Zhang; B. Stein; S. Heineking, eds.) (2026). 15(9) 71–159.
• Overview of Touché 2026: Argumentation Systems. Kiesel, Johannes; Feger, Marc; Hagen, Tim; Heineking, Sebastian; Heinrich, Maximilian; Fröbe, Maik; Boland, Katarina; Pertsch, Wilhelm; Romberg, Julia; Zelch, Ines; Dietze, Stefan; Hagen, Matthias; Potthast, Martin; Stein, Benno in Lecture Notes in Computer Science, R. Campos, A. Jatowt, Y. Lan, M. Aliannejadi, C. Bauer, S. MacAvaney, Z. Ren, S. Verberne, N. Bai, M. Mansoury (eds.) (2026). (Vol. 16485) 277–286.
• Data Annotations as Pedagogical Hints:From Subjective Labels to Critical Thinking. Raumanns, Ralf; Elstner, Theresa; Ferger-Andrews, Louis; Carlsen, Louise M.; Potthast, Martin; Schouten, Josien P. W. Pluim Gerard; Cheplygina, Veronika (2026). 2607.20149
• A Collection of Systematic Reviews in Computer Science. Achkar, Pierre; Gollub, Tim; Potthast, Martin in CEUR Workshop Proceedings, I. Frommholz, C. K. Kreutz, P. Mayr, G. Cabanac (eds.) (2026). (Vol. 4187) 71–77.
• Creating Specialized RAG-Based Search Engines Using the Open Web Index. Nussbaumer, Alexander; Dinzinger, Michael; Heineking, Sebastian; Hendriksen, Gijs; Holz, Felix; Zerhoudi, Saber; Potthast, Martin; Granitzer, Michael in Lecture Notes in Computer Science (2026).
• Humans, LLMs, and Measures Do Not Align in Attributed Information Retrieval. Gienapp, Lukas; Lang, Jenny; Potthast, Martin; Scells, Harrisen (2026).
• Representation Fidelity:Auditing Algorithmic Decisions About Humans Using Self-Descriptions. Elstner, Theresa; Potthast, Martin (2026). 2603.05136
• Detecting RAG Advertisements Across Advertising Styles. Heineking, Sebastian; Pertsch, Wilhelm; Zelch, Ines; Bevendorff, Janek; Stein, Benno; Hagen, Matthias; Potthast, Martin (2026). abs/2603.04925
• An Open SERP Mining Infrastructure for the Archive Query Log. Merker, Jan Heinrich; Ruth, Simon; Scells, Harrisen; Potthast, Martin in Lecture Notes in Computer Science, R. Campos, A. Jatowt, Y. Lan, M. Aliannejadi, C. Bauer, S. MacAvaney, A. Anand, Z. Ren, S. Verberne, N. Bai, M. Mansoury (eds.) (2026). (Vol. 16486) 561–577.
• Affirmative Kritik: Wie Tech-CEOs Ethik als Verkaufsmasche nutzen. Geuter, Jürgen (2026).

  Seit der „KI“-Boom im vollen Gange ist, veröffentlichen alle paar Monate leitende Angestellte und die Geschäftsführer der großen „KI“-Labs wie OpenAI oder Anthropic Manifeste über die existenziellen Gefahren von „KI“, oft flankiert von einigen Wissenschaftler:innen und befreundeten NGO-Vertreter:innen. Es geht um die Notwendigkeit einer Pause in der Entwicklung solcher Systeme oder darum, dass neue Regulierung und soziale Praktiken zum Umgang mit solchen Systemen notwendig seien.
• Hierarchical Background Knowledge in FCA via Must-Link-Before Constraints. Gutekunst, Klara M.; Dürrschnabel, Dominik; Schneider, Stefan; Potthast, Martin (2026).
• A Pipeline to Bootstrap the Evaluation of Retrieval-Augmented Generation for the Automation of Systematic Reviews in Computer Science. Achkar, Pierre; Gollub, Tim; Simons, Arno; Scells, Harrisen; Fröbe, Maik; Potthast, Martin E. Yang, D. Lawrie, S. MacAvaney, J. Mayfield, L. Soldaini, A. Yates (eds.) (2026). 65–70.
• Investigating Counterclaims in Causality Extraction from Text. Hagen, Tim; Deckers, Niklas; Wolter, Felix; Scells, Harrisen; Potthast, Martin (2026). abs/2510.08224
• Relaxed Term Matching for Neural Axiomatic Diagnostics. Parry, Andrew; Fröbe, Maik; Potthast, Martin; MacAvaney, Sean; Stein, Benno; Hagen, Matthias; Ganguly, Debasis A. Moffat, F. Scholer, K. Bi, C. L. A. Clarke (eds.) (2026). 274–284.
• Auto-Judge: A Cross-Task Benchmark for Comparing LLM Judges for Citation-Grounded RAG Systems. Farzi, Naghmeh; Hagen, Tim; Yang, Eugene; Fröbe, Maik; Pradeep, Ronak; Rahmani, Hossein A.; Wang, Xi; Zendel, Oleg; Potthast, Martin; Dietz, Laura A. Moffat, F. Scholer, H. Bast, M. Najork, M. Zhang (eds.) (2026). 3159–3166.
• Relationships between human energy and work‐related constructs: A meta‐analysis. Schmitt, Antje; Sandra Ohly, Sandra; Kleine, Anne‐Kathrin; Schnafel, Ann‐Kathrin (2026). 75(1) e70073.
• Analyzing the role of family socio-economic status, education and work characteristics in times of generative artificial intelligence and digital divide. Neufeld, K.; Ohly, S.; Sedefoglu-Ulucak, D.; Steinhardt, I.; Mauermeister, S. (2026). 31(3) 354–372.
• Empathy in leadership communication: Experimental evidence from two vignette studies on AI’s role in message improvement and observers’ perceptions. Sedefoglu-Ulucak, D.; Ohly, S.; Schmelz, J. (2026). 185 109096.
• A.I., Journalism and the Uncertain Future of the Public Square. Sulzberger, Arthur Gregg (2026).

  Publisher A.G. Sulzberger warns A.I. companies are violating settled law and urges news organizations to stand up for their rights to ensure a sustainable future for reporting.
• Care: Sorge als Gegenstand, Theorie, Methode und Ethik der Wissenschafts- und Technikforschung. Ochs, Casten; Wenten, Klara-Aylin A. Krüger, J.-F. Schrape, C. Schubert, J. Schubert (eds.) (2026). 101–118.
• Drosophila melanogaster Fly Odors Alone are not Sufficient to Attract other Flies. Unni, Anjana Pisharody; Rihani, Karen; Sachse, Silke; Hansson, Bill S; Knaden, Markus (2026). 52(4)
• Nice to Need You! Psychological need fulfillment, well-being, and technology acceptance in human--robot interaction across contexts. Klier, Chantal; Lugrin, Birgit (2026). 9 100368.
• Current morphodynamics and subsurface structure of thrust moraines and rock glaciers connected to three Little Ice Age glacier forefields in the Swiss Alps. Kunz, J.; Buchelt, S.; Wiegand, T.; Ullmann, T.; Kneisel, C. (2026). 20(8) 4255–4275.
• SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models. Su, Binxian; Lou, Haoye; Zhu, Shucheng; Wang, Weikang; Liu, Ying; Yu, Dong; Liu, Pengyuan M. Liakata, V. P. Moreira, J. Zhang, D. Jurgens (eds.) (2026). 1222–1251.
• Evaluating the Efficiency and Effectiveness of Learned Sparse Retrieval with the lsr_benchmark. Fröbe, Maik; Schlatt, Ferdinand; Rulli, Cosimo; Hagen, Tim; Merker, Jan Heinrich; Hendriksen, Gijs; Lassance, Carlos; Nardini, Franco Maria; Venturini, Rossano; Potthast, Martin in Lecture Notes in Computer Science (2026).
• Topic-Specific Classifiers are Better Relevance Judges than Prompted LLMs. Gienapp, Lukas; Potthast, Martin; Yates, Andrew; Scells, Harrisen; Yang, Eugene (2026).
• Does unauthorized immigration drive community crime rates? Evidence from 11,500 U.S. neighborhoods. Kubrin, Charis E.; Christopher, Derek; Hodgen, Cheyenne; Luo, Xiaoshuang Iris; Hipp, John R. (2026). 1–18.

  Research on the immigration-crime nexus has grown substantially, yet few studies differentiate among immigrants of different legal statuses, including undocumented immigrants. Of those that do, analyses are conducted at state and metropolitan area levels, leaving unanswered the question of how the presence of undocumented immigrants is associated with neighborhood crime rates—our focus. To construct neighborhood-level estimates of the undocumented population, we access restricted-use individual-level Census data, where tract of residence can be identified, and apply an imputation procedure. We combine these estimates with a dataset containing crime information for roughly 11,500 neighborhoods across U.S. cities over a decade. Controlling for change in foreign-born citizens and lawful permanent residents as well as other correlates of community crime rates, we estimate neighborhood-level fixed effects models to determine how change in undocumented residents is associated with change in violent and property crime levels between 2010 and 2018. We find that neighborhoods that experienced greater increases in the share of undocumented residents saw greater reductions in property crime and no detectable change in violent crime. We also document distinct patterns in which increasing undocumented residents is associated with decreasing aggravated assaults but increasing robberies, consistent with a possible victimization explanation.
• GIS ANALYSIS OF LINEAR AND SPIRAL GEOMETRIES IN THE BOSNIAN VALLEY OF THE PYRAMIDS. Osmanagich, Sam (2026).
• From Keyterms to Context: Exploring Topic Description Generation in Scientific Corpora. Achkar, Pierre; Murugaboopathy, Satiyabooshan; Kreuter, Anne; Gollub, Tim; Potthast, Martin; Campbell, Yuri Y. Dong, W. Xiao, H. Zhang, R. Zhang, O. Ernst, L. Wang, F. Liu (eds.) (2025).
• The Mechanisms of Agile Management Wenten, Klara-Aylin (2025). Routledge, London.
• Counterfactual Query Rewriting to Use Historical Relevance Feedback. Keller, Jüri; Fröbe, Maik; Hendriksen, Gijs; Alexander, Daria; Potthast, Martin; Hagen, Matthias; Schaer, Philipp in Lecture Notes in Computer Science, C. Hauff, C. Macdonald, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). (Vol. 15574) 138–147.
• Jenseits der Logik der Empfehlung. Formale Begriffsanalyse als Grundlage für eine neue Variante zur Vermittlung von Nutzenden und journalistischen Inhalten. Uhlmann, Markus; Hirth, Johannes; Horn, Viktoria (2025). 137–155.
• A Test Collection for Dataset Retrieval. Kolyada, Nikolay; Stein, Benno; Potthast, Martin in Lecture Notes in Computer Science, C. Hauff, C. Macdonal, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). (Vol. 15576) 372–380.
• Perspektiven zur (Neu-)Bestimmung soziodigitaler Autonomie und Privatheit. Uhlmann, Markus (2025). 49(3)
• Overview of the Plagiarism Detection Task at PAN 2025. Greiner-Petter, André; Fröbe, Maik; Wahle, Jan Philip; Ruas, Terry; Gipp, Bela; Aizawa, Akiko; Potthast, Martin in CEUR Workshop Proceedings, G. Faggioli, N. Ferro, P. Rosso, D. Spina (eds.) (2025). (Vol. 4038) 3575–3585.
• Web-scale Retrieval Experimentation with chatnoir-pyterrier. Merker, Jan Heinrich; Bevendorff, Janek; Fröbe, Maik; Hagen, Tim; Scells, Harrisen; Wiegmann, Matti; Stein, Benno; Hagen, Matthias; Potthast, Martin in Lecture Notes in Computer Science, C. Hauff, C. Macdonal, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). (Vol. 15576) 96–104.
• Dynamiken digitaler Bewertung. Über Gestaltungsspielräume in Infrastrukturen – von KI bis Queering Krenn, Karoline; Kropf, Jonathan; Laser, Stefan; Ochs, Carsten (2025). Springer VS, Wiesbaden.
• „Mit einer KI bleibe ich in dem Kosmos an Informationen gefangen, die ich schon habe.“ Im Gespräch mit dem Produktbewerter Holger Brackemann von der Stiftung Warentest. Krenn, Karoline; Kropf, Jonathan K. Krenn, J. Kropf, S. Laser, C. Ochs (eds.) (2025). 119–133.
• Creating the “Casual Listener”: Consecrating Institutions and Spotify’s “Curational Turn”. Kropf, Jonathan R. Diaz-Bone, A. Lehmann-Wermser (eds.) (2025). 293–312.
• Artificial Intelligence as a Hybrid Life Form. On the Critique of Cybernetic Expansion. Lamla, Jörn I. Spiecker gen. Döhmann, C. Burchard (eds.) (2025). 331–353.
• Machbarkeitsstudie für ein Bundesinstitut für Verbraucherforschung. Abschlussbericht einer vom Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz in Auftrag gegebenen „Studie zur Weiterentwicklung der Verbraucherforschung durch Einrichtung eines Bundesinstituts für Verbraucherforschung“ Kenning, Peter; Christian, Kastrop; Lamla, Jörn; Reisch, Lucia (2025).
• Ranking Generated Answers: On the Agreement of Retrieval Models with Humans on Consumer Health Questions. Heineking, Sebastian; Probst, Jonas; Steinbach, Daniel; Potthast, Martin; Scells, Harrisen C. Hauff, C. Macdonal, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). 128–137.
• Digitale Resonanz – oder: Wie KI Dinge zum Klingen bringt. Anmerkungen zur Politischen Ontologie bei Rosa und Latour. Lamla, Jörn B. Hollstein, J. Oberthür (eds.) (2025). 514–522.
• Pricing, Design and Cultivation – Conceptual Tools for the Normative Assessment of Fairness in the Age of Media Platformization. Kropf, Jonathan; Lamla, Jörn; Uhlmann, Markus (2025).
• Konsum. Lamla, Jörn; Roschka, Jakob M. Endreß, B. Rampp (eds.) (2025). 523–527.
• The Future of Consumption. Agenda for a new perspective on consumer Research. Lamla, Jörn; Heidbrink, Ludger; Hohnsträter, Dirk; Loer, Kathrin; Roschka, Jakob (2025).
• Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders. Schlatt, Ferdinand; Fröbe, Maik; Scells, Harrisen; Zhuang, Shengyao; Koopman, Bevan; Zuccon, Guido; Stein, Benno; Potthast, Martin; Hagen, Matthias in Lecture Notes in Computer Science, C. Hauff, C. Macdonal, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). (Vol. 15573) 1–19.
• Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-ranking. Schlatt, Ferdinand; Fröbe, Maik; Scells, Harrisen; Zhuang, Shengyao; Koopman, Bevan; Zuccon, Guido; Stein, Benno; Potthast, Martin; Hagen, Matthias in Lecture Notes in Computer Science, C. Hauff, C. Macdonal, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). (Vol. 15574) 323–334.
• Kursorischer Vergleich der Übersetzungsdienste ChatGPT, Google Translate, DeepL und eTranslation Hagen, Tim; Potthast, Martin (2025).
• ARCHITECTURAL PATTERNS AND PERFORMANCE ANALYSIS OF INTEGER SURROGATE KEYS FOR TIME-SERIES DATA WAREHOUSING. Stumpf, Sviatoslav; Povyshev, Vladislav (2025). 8(12) e81638.

  The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.
• ImageCLEF 2025: Multimedia Retrieval in Medical, Social Media and Content Recommendation Applications. Ionescu, Bogdan; Müller, Henning; Stanciu, Dan-Cristian; Idrissi-Yaghir, Ahmad; Radzhabov, Ahmedkhan; de Herrera, Alba García Seco; Andrei, Alexandra; Storr as, Andrea; Ben Abacha, Asma; Bracke, Benjamin; Lecouteux, Benjamin; Stein, Benno; Macaire, Cécile; Friedrich, Christoph M.; Schmidt, Cynthia Sabrina; Fabre, Diandra; Schwab, Didier; Dimitrov, Dimitar; Esperanc ca-Rodier, Emmanuelle; Constantin, Gabriel; Becker, Helmut; Damm, Hendrik; Schäfer, Henning; Rodkin, Ivan; Koychev, Ivan; Kiesel, Johannes; Rückert, Johannes; Malvehy, Josep; textcommabelowStefan, Liviu-Daniel; Bloch, Louise; Potthast, Martin; Heinrich, Maximilian; Riegler, Michael A.; Dogariu, Mihai; Codella, Noel; Halvorsen, Pr al; Nakov, Preslav; Brüngel, Raphael; Novoa, Roberto Andres; Das, Rocktim Jyoti; Hicks, Steven A.; Gautam, Sushant; Pakull, Tabea M. G.; Thambawita, Vajira; Kovalev, Vassili; Yim, Wen-Wai; Xie, Zhuohan in Lecture Notes in Computer Science, C. Hauff, C. Macdonal, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). (Vol. 15576) 398–406.
• Dynamiken digitaler Bewertung. Ein Vorschlag zur Sortierung. Krenn, Karoline/; Kropf, Jonathan; Laser, Stefan; Ochs, Carsten K. Krenn, J. Kropf, S. Laser, C. Ochs (eds.) (2025). 1–27.
• Humane work design: How does the digitization of work change core work characteristics in different occupations?. Ohly, Sandra; Granica, Amina; Herwig, Hannes; Kühlewind, Niklas; Paetzold, Tobias; Vinhoven, Lana; Wiemers, Luisa; Zhang, Xi (2025). 79(4) 569–580.
• Large Language Model Relevance Assessors Agree With One Another More Than With Human Assessors. Fröbe, Maik; Parry, Andrew; Schlatt, Ferdinand; MacAvaney, Sean; Stein, Benno; Potthast, Martin; Hagen, Matthias N. Ferro, M. Maistro, G. Pasi, O. Alonso, A. Trotman, S. Verberne (eds.) (2025). 2858–2863.
• Team OpenWebSearch at LongEval: Using Historical Data for Scientific Search. Alexander, Daria; Fröbe, Maik; Hendriksen, Gijs; Hagen, Matthias; Hiemstra, Djoerd; Potthast, Martin; Vries, Arjen in CEUR Workshop Proceedings, G. Faggioli, N. Ferro, P. Rosso, D. Spina (eds.) (2025). (Vol. 4038) 3316–3326.
• Simplified Longitudinal Retrieval Experiments: A Case Study on Query Rewriting and Document Boosting. Keller, Jüri; Fröbe, Maik; Hendriksen, Gijs; Alexander, Daria; Potthast, Martin; Schaer, Philipp in Lecture Notes in Computer Science, J. Carrillo-de-Albornoz, A. G. S. Herrera, J. Gonzalo, L. Plaza, J. Mothe, F. Piroi, P. Rosso, D. Spina, G. Faggioli, N. Ferro (eds.) (2025). (Vol. 16089) 117–127.
• The German Commons -- 154 Billion Tokens of Openly Licensed Text for German Language Models. Gienapp, Lukas; Schröder, Christopher; Schweter, Stefan; Akiki, Christopher; Schlatt, Ferdinand; Zimmermann, Arden; Genêt, Phillipe; Potthast, Martin (2025). abs/2510.13996
• Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature Summarization. Achkar, Pierre; Gollub, Tim; Potthast, Martin in CEUR Workshop Proceedings, I. Frommholz, P. Mayr, G. Cabanac, S. Verberne, C. K. Kreutz (eds.) (2025).
• Overview of Touché 2025: Argumentation Systems. Kiesel, Johannes; c Cau gri c Cöltekin; Gohsen, Marcel; Heineking, Sebastian; Heinrich, Maximilian; Fröbe, Maik; Hagen, Tim; Aliannejadi, Mohammad; Anand, Sharat; Erjavec, Tomavz; Hagen, Matthias; Kopp, Matyávs; Ljubevsi’c, Nikola; Meden, Katja; Mirzakhmedova, Nailia; Morkevivcius, Vaidas; Scells, Harrisen; Wolter, Moritz; Zelch, Ines; Potthast, Martin; Stein, Benno in Lecture Notes in Computer Science, J. C. de Albornoz, J. Gonzalo, L. Plaza, A. García Seco de Herrera, J. Mothe, F. Piroi, P. Rosso, D. Spina, G. Faggioli, N. Ferro (eds.) (2025).
• Effects of task switching on depletion, motivation, and creativity: Examining the nature of tasks. Nuhn, Christina; Ohly, Sandra (2025).
• Overview of the ``Voight-Kampff’’ Generative AI Authorship Verification Task at PAN and ELOQUENT 2025. Bevendorff, Janek; Wang, Yuxia; Karlgren, Jussi; Wiegmann, Matti; Fröbe, Maik; Tsivgun, Akim; Su, Jinyan; Xie, Zhuohan; Abassy, Mervat; Mansurov, Jonibek; Xing, Rui; Ta, Minh Ngoc; Elozeiri, Kareem Ashraf; Gu, Tianle; Tomar, Raj Vardhan; Geng, Jiahui; Artemova, Ekaterina; Shelmanov, Artem; Habash, Nizar; Stamatatos, Efstathios; Gurevych, Iryna; Nakov, Preslav; Potthast, Martin; Stein, Benno in CEUR Workshop Proceedings, G. Faggioli, N. Ferro, P. Rosso, D. Spina (eds.) (2025). (Vol. 4038) 3504–3534.
• Learning Effective Representations for Retrieval Using Self-Distillation with Adaptive Relevance Margins. Gienapp, Lukas; Deckers, Niklas; Potthast, Martin; Scells, Harrisen H. Zamani, L. Dietz, B. Piwowarski, S. Bruch (eds.) (2025). 275–285.
• Axioms for Retrieval-Augmented Generation. Merker, Jan Heinrich; Fröbe, Maik; Stein, Benno; Potthast, Martin; Hagen, Matthias H. Zamani, L. Dietz, B. Piwowarski, S. Bruch (eds.) (2025). 67–77.
• ReNeuIR at SIGIR 2025: The Fourth Workshop on Reaching Efficiency in Neural Information Retrieval. Bruch, Sebastian; Fröbe, Maik; Hagen, Tim; Nardini, Franco Maria; Potthast, Martin N. Ferro, M. Maistro, G. Pasi, O. Alonso, A. Trotman, S. Verberne (eds.) (2025). 4153–4156.
• Overview of PAN 2025: Voight-Kampff Generative AI Detection, Multilingual Text Detoxification, Multi-Author Writing Style Analysis, and Generative Plagiarism Detection. Bevendorff, Janek; Dementieva, Daryna; Fröbe, Maik; Gipp, Bela; Greiner-Petter, André; Karlgren, Jussi; Mayerl, Maximilian; Nakov, Preslav; Panchenko, Alexander; Potthast, Martin; Shelmanov, Artem; Stamatatos, Efstathios; Stein, Benno; Wang, Yuxia; Wiegmann, Matti; Zangerle, Eva in Lecture Notes in Computer Science, J. C. de Albornoz, J. Gonzalo, L. Plaza, A. G. S. Herrera, J. Mothe, F. Piroi, P. Rosso, D. Spina, G. Faggioli, N. Ferro (eds.) (2025). (Vol. 16089) 388–411.
• Call for Research on the Impact of Information Retrieval on Social Norms. Gollub, Tim; Achkar, Pierre; Potthast, Martin; Stein, Benno in Lecture Notes in Computer Science, C. Hauff, C. Macdonal, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). (Vol. 15575) 371–384.
• When Do Challenge Stressors Promote Work Motivation? Exploring the Role of Day-Level Self-Efficacy. Prem, Roman; Ohly, Sandra; Weigelt, Oliver; Siestrup, Katja; Kubicek, Bettina (2025). 2025(1) 21972.
• The Viability of Crowdsourcing for RAG Evaluation. Gienapp, Lukas; Hagen, Tim; Fröbe, Maik; Hagen, Matthias; Stein, Benno; Potthast, Martin; Scells, Harrisen N. Ferro, M. Maistro, G. Pasi, O. Alonso, A. Trotman, S. Verberne (eds.) (2025). 159–169.
• TIREx Tracker: The Information Retrieval Experiment Tracker. Hagen, Tim; Fröbe, Maik; Merker, Jan Heinrich; Scells, Harrisen; Hagen, Matthias; Potthast, Martin N. Ferro, M. Maistro, G. Pasi, O. Alonso, A. Trotman, S. Verberne (eds.) (2025). 3764–3771.
• TITE: Token-Independent Text Encoder for Information Retrieval. Schlatt, Ferdinand; Hagen, Tim; Potthast, Martin; Hagen, Matthias N. Ferro, M. Maistro, G. Pasi, O. Alonso, A. Trotman, S. Verberne (eds.) (2025). 2493–2503.
• Mirror, Mirror on the Wall: Enabling Computational Research on Beauty Ideals. Gollub, Tim; Achkar, Pierre; Potthast, Martin; Stein, Benno (2025).
• The Two Paradigms of LLM Detection: Authorship Attribution vs. Authorship Verification. Bevendorff, Janek; Wiegmann, Matti; Richter, Emmelie; Potthast, Martin; Stein, Benno W. Che, J. Nabende, E. Shutova, M. T. Pilehvar (eds.) (2025). 3762–3787.
• Work design and performance. Ohly, Sandra; Venz, Laura (2025). 147–173.
• The Second International Workshop on Open Web Search (WOWS). Farzana, Sheikh; Fröbe, Maik; Granitzer, Michael; Hendriksen, Gijs; Hiemstra, Djoerd; Potthast, Martin; Vries, Arjen; Zerhoudi, Saber in Lecture Notes in Computer Science (2025).
• Corpus Subsampling: Estimating the Effectiveness of Neural Retrieval Models on Large Corpora. Fröbe, Maik; Parry, Andrew; Scells, Harrisen; Wang, Shuai; Zhuang, Shengyao; Zuccon, Guido; Potthast, Martin; Hagen, Matthias in Lecture Notes in Computer Science, C. Hauff, C. Macdonald, D. Jannach, G. Kazai, F. M. Nardini, F. Pinelli, F. Silvestri, N. Tonellotto (eds.) (2025). (Vol. 15572) 453–471.
• Optimisation of Logistic Operations using AI. Levin, Semen (S. Levin, ed.) (2024). 13(2)

  In today's world, optimising logistical operations becomes a defining factor in the success of retailers. The complexity and dynamism of modern supply chains require the application of advanced technologies for accurate demand forecasting and inventory management. Artificial Intelligence (AI) demonstrates immense potential in addressing these challenges, offering a new level of efficiency and adaptability. This research focuses on applying AI to analyse a retailer's operational data to optimise its logistical operations. Utilising analysis models such as SARIMA for time series and random forests for machine learning enabled precise daily sales forecasts, identification of seasonal peaks, and optimisation of inventory levels and delivery route planning. Particular attention was paid to the analysis of variable importance, revealing key factors affecting the efficiency of logistical operations, including historical sales data, weather conditions, distance to delivery locations, and holiday periods. The investigation results show that integrating AI into logistics improves forecast accuracy and inventory management efficiency and contributes to reducing logistical costs and enhancing customer satisfaction by optimising delivery time and costs. The data-driven and AI-based analytical approach provides a comprehensive view of logistics management, demonstrating how technological innovations can transform traditional methods and create a competitive advantage in a dynamic market environment. The research underscores the significance of adopting data and analytics as the basis for strategic planning and decision-making, reinforcing the idea that AI serves as a valuable extension of companies' analytical capabilities in the field of logistics
• Evaluating Moral Beliefs across LLMs through a Pluralistic Framework. Liu, Xuelin; Zhu, Yanfei; Zhu, Shucheng; Liu, Pengyuan; Liu, Ying; Yu, Dong in Findings of ACL, Y. Al-Onaizan, M. Bansal, Y.-N. Chen (eds.) (2024). (Vol. EMNLP 2024) 4740–4760.
• MSDD: A Multimodal Language Dateset for Stance Detection. Hu, Mengyang; Liu, Pengyuan; Wang, Weikang; Zhang, Hu; Lin, Chengxiao in Lecture Notes in Computer Science, Q. Su, G. Xu, X. Yang (eds.) (2022). (Vol. 13495) 112–124.
• Preventing Counterfeit Products using Cryptography, QR Code and Webservice. Shaik, Cheman (2021, February).

  We propose a model of mobile agents to construct social networks, based on a system of moving particles by keeping track of the collisions during their permanence in the system. We reproduce not only the degree distribution, clustering coefficient and shortest path length of a large data base of empirical friendship networks recently collected, but also some features related with their community structure. The model is completely characterized by the collision rate and above a critical collision rate we find the emergence of a giant cluster in the universality class of two-dimensional percolation. Moreover, we propose possible schemes to reproduce other networks of particular social contacts, namely sexual contacts.
• 基于规则的双重否定识别 - - 以"不v1不v2"为例(Double Negative Recognition Based on Rules - - Taking "不v1不v2" as an Example). Wang, Yu M. Sun, S. Li, Y. Zhang, Y. Liu (eds.) (2020). 1–9.
• 基于强负采样的词嵌入优化算法(Word Embedding Optimization Based on Hard Negative Sampling). Wang, Yuchen; Lin, Miaozhe; Zhan, Jiefan M. Sun, S. Li, Y. Zhang, Y. Liu (eds.) (2020). 207–214.
• 联合依存分析的汉语语义组合模型(Chinese Semantic Composition Model with Dependency Parsing). Chen, Yuanmeng; Zhang, Yujie; Xu, Jinan; Chen, Yufeng M. Sun, S. Li, Y. Zhang, Y. Liu (eds.) (2020). 215–224.
• 基于BERT的端到端中文篇章事件抽取(A BERT-based End-to-End Model for Chinese Document-level Event Extraction). Zhang, Hongkuan; Song, Hui; Wang, Shuyi; Xu, Bo M. Sun, S. Li, Y. Zhang, Y. Liu (eds.) (2020). 390–401.
• A Study on the Classification of Chinese Interrogatives Based on Pragmatic Functions. Li, Jiangtao; Rao, Gaoqi in Lecture Notes in Computer Science, M. Liu, C. Kit, Q. Su (eds.) (2020). (Vol. 12278) 734–746.
• BIPRE: Bi-directional Inter-Personal Relationship Extraction Task. Tian, Yongsheng; Liu, Pengyuan; Du, Bingjie in Lecture Notes in Computer Science, M. Liu, C. Kit, Q. Su (eds.) (2020). (Vol. 12278) 640–651.
• A Dual Layer Regression Model for Cross-border E-commerce Industry Sale and Hot Product Prediction. Luo, Wangda; Su, Hang; Liu, Yuhan; Xu, Ruifeng in Lecture Notes in Computer Science, Y. Yang, L. Yu, L.-J. Zhang (eds.) (2020). (Vol. 12408) 50–61.
• 半监督跨领域语义依存分析技术研究(Semi-supervised Domain Adaptation for Semantic Dependency Parsing). Mao, Dazhan; Li, Huayong; Shao, Yanqiu M. Sun, S. Li, Y. Zhang, Y. Liu (eds.) (2020). 783–794.
• Chinese and English Elementary Discourse Units Segmentation based on Bi-LSTM-CRF Model. Li, Yancui; Lai, Chunxiao; Feng, Jike; Feng, Hongyu M. Sun, S. Li, Y. Zhang, Y. Liu (eds.) (2020). 1068–1078.
• Adaptive Vocabulary Construction for Frustration Intensity Modelling in Customer Support Dialog Texts Zuters, Janis; Leonova, Viktorija (2020). (Vol. 169) Springer.
• 发音属性优化建模及其在偏误检测的应用(Speech attributes optimization modeling and application in mispronunciation detection). Guo, Minghao; Xie, Yanlu M. Sun, S. Li, Y. Zhang, Y. Liu (eds.) (2020). 66–76.
• EXACT SOLUTIONS OF SCHRÖDINGER EQUATION WITH SOLVABLE POTENTIALS FOR NON PT/PT-SYMMETRIC. Antia, Akaninyene D. (2015). (Vol. 4) 47–54.

  We have obtained explicitly the exact solutions of the Schrodinger equation with Non PT/PT symmetric Rosen Morse II, Scarf II and Coulomb potentials. Energy eigenvalues and the corresponding unnormalized wave functions for these systems for both Non PT and PT symmetric are also obtained using the Nikiforov-Uvarov (NU) method.
• MORPES: A Model for Personalized Rendering of Web Content on Mobile Devices. K.S.Kuppusamy1; and G.Aghila2 W. Broll, C. Greenhalgh, E. F. Churchill (eds.) (2012). 47–54.
• A Novel Dencos Model For High Dimensional Data Using Genetic Algorithms. Vijayakumar, T.; V.Nivedhitha; K.Deeba; Bama, M. Sathya (2012). 2(1) 35–43.

  We propose a model of mobile agents to construct social networks, based on a system of moving particles by keeping track of the collisions during their permanence in the system. We reproduce not only the degree distribution, clustering coefficient and shortest path length of a large data base of empirical friendship networks recently collected, but also some features related with their community structure. The model is completely characterized by the collision rate and above a critical collision rate we find the emergence of a giant cluster in the universality class of two-dimensional percolation. Moreover, we propose possible schemes to reproduce other networks of particular social contacts, namely sexual contacts.