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Personalized LoRA for Human-Centered Text Understanding
March 12, 2024, 4:51 a.m. | You Zhang, Jin Wang, Liang-Chih Yu, Dan Xu, Xuejie Zhang
cs.CL updates on arXiv.org arxiv.org
Abstract: Effectively and efficiently adapting a pre-trained language model (PLM) for human-centered text understanding (HCTU) is challenging since user tokens are million-level in most personalized applications and do not have concrete explicit semantics. A standard and parameter-efficient approach (e.g., LoRA) necessitates memorizing numerous suits of adapters for each user. In this work, we introduce a personalized LoRA (PLoRA) with a plug-and-play (PnP) framework for the HCTU task. PLoRA is effective, parameter-efficient, and dynamically deploying in PLMs. …
arxiv cs.cl human lora personalized text text understanding type understanding
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