García López, Iván MiguelRamírez Montoya, María SoledadMolina Espinosa, José Martín2024-09-212024-09-212024-10-23García-López, I.M., Ramírez-Montoya, M.S. & Molina-Espinosa, J.M. (2024). Reg-ulatory Challenges and Optimization Strategies for Open Large Language Models: A Multidimensional Framework for Efficient Management. 12th edition of the Techno-logical Ecosystems for Enhancing Multiculturality (TEEM 2024), Alicante, Spain.https://hdl.handle.net/11285/676995Innovations in artificial intelligence are rapidly transforming various in-dustries, particularly through the development and deployment of Open Large Language Models (OLLMs). However, the absence of a robust regula-tory framework presents significant challenges in ensuring the ethical, safe, and effective use of these models. This research aims to address this gap by proposing a comprehensive regulatory framework designed to optimize the scalability and performance of OLLMs, emphasizing the importance of structured pruning techniques. By integrating both quantitative and qualita-tive analyses, the study will assess the technical capabilities and societal implications of OLLMs, ultimately providing clear guidelines that promote responsible and sustainable innovation. The expected outcomes include the development of a governance model that balances the need for innovation with ethical considerations, offering a pathway for the regulation of OLLMs that supports their continued evolution while safeguarding public interests.TextoengrestrictedAccesshttp://creativecommons.org/licenses/by/4.0HUMANIDADES Y CIENCIAS DE LA CONDUCTAEducationConferenciaProceedings of TEEM 2024. TEEM 2024. Lecture Notes in Educational Technologyhttps://orcid.org/0000-0001-9219-4970https://orcid.org/0000-0002-1274-7061https://orcid.org/0000-0002-4118-6951open large language modelartificial intelligenceopen frameworkhigher educationeducational innovationR4C§TEEspaña / Spain