Leveraging Large Language Models (LLMs) for recommendation has recently garnered
considerable attention, where fine-tuning plays a key role in LLMs' adaptation. However, the …

Personalized recommendation serves as a ubiquitous channel for users to discover
information tailored to their interests. However, traditional recommendation models primarily …

Adapters, a plug-in neural network module with some tunable parameters, have emerged as
a parameter-efficient transfer learning technique for adapting pre-trained models to …