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Found 6 papers, 6 papers with code
IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT
This is also a notable improvement over the Adapter and LoRA, which require 37-39 GB GPU memory and 350-380 seconds per epoch for training.
An Empirical Study of Training ID-Agnostic Multi-modal Sequential Recommenders
Sequential Recommendation (SR) aims to predict future user-item interactions based on historical interactions.
A Content-Driven Micro-Video Recommendation Dataset at Scale
Micro-videos have recently gained immense popularity, sparking critical research in micro-video recommendation with significant implications for the entertainment, advertising, and e-commerce industries.
NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation
The development of TransRec has encountered multiple challenges, among which the lack of large-scale, high-quality transfer learning recommendation dataset and benchmark suites is one of the biggest obstacles.
Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights
If yes, we benchmark these existing adapters, which have been shown to be effective in NLP and CV tasks, in item recommendation tasks.
Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited
In fact, this question was answered ten years ago when IDRec beats MoRec by a strong margin in both recommendation accuracy and efficiency.
