IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT

Author:

Fu Junchen1ORCID,Ge Xuri1ORCID,Xin Xin2ORCID,Karatzoglou Alexandros3ORCID,Arapakis Ioannis4ORCID,Wang Jie1ORCID,Jose Joemon M.1ORCID

Affiliation:

1. University of Glasgow, Glasgow, United Kingdom

2. Shandong University, Qingdao, China

3. Amazon, Barcelona, Spain

4. Telefonica Research, Barcelona, Spain

Publisher

ACM

Reference85 articles.

1. Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023. Gpt-4 technical report. arXiv preprint arXiv:2303.08774 (2023).

2. Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, and Xiangnan He. 2023. Tallrec: An effective and efficient tuning framework to align large language model with recommendation. arXiv preprint arXiv:2305.00447 (2023).

3. Tom Brown et al. 2020. Language models are few-shot learners. Advances in neural information processing systems Vol. 33 (2020) 1877--1901.

4. Tinytl: Reduce memory, not parameters for efficient on-device learning;Cai Han;Advances in Neural Information Processing Systems,2020

5. Strategies to achieve a carbon neutral society: a review

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