Feb. 12, 2024, 5:43 a.m. | Xiangyu Chang Sk Miraj Ahmed Srikanth V. Krishnamurthy Basak Guler Ananthram Swami Samet Oymak Amit K.

cs.LG updates on arXiv.org arxiv.org

Parameter-efficient tuning (PET) methods such as LoRA, Adapter, and Visual Prompt Tuning (VPT) have found success in enabling adaptation to new domains by tuning small modules within a transformer model. However, the number of domains encountered during test time can be very large, and the data is usually unlabeled. Thus, adaptation to new domains is challenging; it is also impractical to generate customized tuned modules for each such domain. Toward addressing these challenges, this work introduces PLUTO: a Plug-and-pLay modUlar …

cs.ai cs.lg data domains enabling found lora modules pet prompt prompt tuning small success test transformer transformer model visual

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