Open-source research
IISAN-Versa
A decoupled parameter-efficient adaptation framework for symmetric and asymmetric multimodal foundation models in recommendation.
- Year
- 2025
- Status
- active
- Focus
- Python · PEFT · Sequential Recommendation
What it does
IISAN-Versa adapts multimodal foundation models for sequential recommendation while reducing the memory and training costs associated with full fine-tuning.
Its decoupled side-adapter design supports both symmetric and asymmetric text-image encoder combinations. The project also covers alignment between encoders with different depths and representation dimensions.
Evidence and scope
This page is a concise guide to the work. Use the primary paper for the experimental setup, quantitative results, limitations, and formal claims; use the repository for the implementation and current reproduction instructions.