Programme

Chair: Martin Stierle, University of Luxembourg

Chair: Justyna Ożegalska-Trybalska, Jagiellonian University

Chair: Johanna Vanderstraeten, University of Antwerp

Chair: Keith Maskus, University of Colorado, Boulder

Chair: Irene Calboli, Texas A&M University School of Law

Chair: Caterina Sganga, Scuola Superiore Sant'Anna - Pisa

Chair: Arina Gorbatyuk, KU Leuven and EDSON

Turning UPC Ambitions into Action: Recent developments in UPC case law, key challenges and building trust in the UPC. Chair: Rochelle Dreyfuss, emerita professor NYU

Speakers: Richard David Arnold, Sam Granata, Michaël Beck, Verena Bertram, Volkmar Henke. Chair: Rochelle Dreyfuss, emerita professor NYU

Speakers: Aleš Zalar, Flip Petillion, Chiara Accornero, Karin Kuhl. Chair: Arina Gorbatyuk (KU Leuven and Sirius Legal)

Speakers: Laurent Manderieux, Josef Drexl, Yann Ménière, Vladia Borissova. Chair: Irene Calboli, Texas A&M University School of Law

Chair: Amandine Leonard, University of Edinburgh, Law School

Chair: Justyna Ożegalska-Trybalska, Jagiellonian University

Chair: Orit Fischman Afori, College of Managemement

Chair: Simon Geiregat, GIPLI, Ghent University

Chair: Brent Lutes, US Copyright Office

The recent evolution of Large Language Models (LLMs) - and AI more broadly - is already transforming the research landscape, not only in the field of Intellectual Property (IP). These technologies present new methodological opportunities to overcome longstanding challenges, such as automating large scale text analysis (e.g. from court case documents). Also, for patent offices (and IP practitioners), the use of LLMs promises enormous potential, but not without challenges. LLMs not only promise to support the scaling of prior art analysis, enhancing patent landscaping, and mapping technological convergence (Aristodemou and Tietze, 2018; Aristodemou, 2020). At the same time, and particularly so for rigorous research, LLMs introduce new methodological complexities that merit collective scrutiny and dialogue. The community has not yet established standardized procedures and guidelines for the rigorous use of LLMs in research. This themed session will explore how especially LLMs (e.g. GPT-4 and open-source models) are reshaping empirical IP research methods broadly, i.e. not limited to patent research. It bring stogether contributions that showcase novel applications, critically examine methodological advances, and highlight best practices and challenges. Emphasis is placed on both academic studies and institutional deployments (e.g. by patent offices, firms, or intergovernmental organisations), fostering mutual learning across sectors. Emerging work at the intersection of LLMs and IP, including automated litigation text analysis, semantic prior art search, technology foresight, trademark studies, and SDG-related IP mapping, are also of interest. Chair: Frank Tietze, University of Cambridge Discussants: Justin Jütte, University College DublinValerio Sterzi, University of BordeauxJoost Poort, University of AmsterdamLeonidas Aristodemou, University of Cambridge

Pre-registration is required for all social activities.