3 papers
cs.IR2025
Inference Computation Scaling for Feature Augmentation in Recommendation Systems
Weihao Liu, Zhaocheng Du, Haiyuan Zhao +5
Large language models have become a powerful method for feature augmentation in recommendation systems. However, existing approaches relying on quick inference often suffer from in…
cs.CL2025
Few-shot LLM Synthetic Data with Distribution Matching
Jiyuan Ren, Zhaocheng Du, Zhihao Wen +4
As large language models (LLMs) advance, their ability to perform in-context learning and few-shot language generation has improved significantly. This has spurred using LLMs to pr…
cs.IR2025
CreAgent: Towards Long-Term Evaluation of Recommender System under Platform-Creator Information Asymmetry
Xiaopeng Ye, Chen Xu, Zhongxiang Sun +4
Ensuring the long-term sustainability of recommender systems (RS) emerges as a crucial issue. Traditional offline evaluation methods for RS typically focus on immediate user feedba…