An empirical study on parameter-efficient fine-tuning for multimodal large language models

Zhou, Xiongtao, He, Jie, Ke, Yuhua, Zhu, Guangyao, Gutierrez Basulto, Victor ORCID: https://orcid.org/0000-0002-6117-5459 and Pan, Jeff Z. 2024. An empirical study on parameter-efficient fine-tuning for multimodal large language models. Presented at: 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Bangkok, Thailand, 11-16 August 2024. Findings of the Association for Computational Linguistics: ACL 2024. Association for Computational Linguistics, pp. 10057-10084. 10.18653/v1/2024.findings-acl.598

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Item Type:	Conference or Workshop Item (Paper)
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	Association for Computational Linguistics
ISBN:	979-889176099-8
Related URLs:	Organisation
Date of First Compliant Deposit:	17 June 2024
Date of Acceptance:	16 May 2024
Last Modified:	17 Feb 2025 14:45
URI:	https://orca.cardiff.ac.uk/id/eprint/169851

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