Search Results for author:
Found 2 papers, 0 papers with code
LLM4SBR: A Lightweight and Effective Framework for Integrating Large Language Models in Session-based Recommendation
However, constrained by high time and space costs, as well as the brief and anonymous nature of session data, the first LLM recommendation framework suitable for industrial deployment has yet to emerge in the field of SBR.
Causally Regularized Learning with Agnostic Data Selection Bias
However, this ideal assumption is often violated in real applications, where selection bias may arise between training and testing process.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
