2 papers
cs.IR2025
Augment or Not? A Comparative Study of Pure and Augmented Large Language Model Recommenders
Wei-Hsiang Huang, Chen-Wei Ke, Wei-Ning Chiu +5
Large language models (LLMs) have introduced new paradigms for recommender systems by enabling richer semantic understanding and incorporating implicit world knowledge. In this stu…
cs.CL2025
Confidence in Large Language Model Evaluation: A Bayesian Approach to Limited-Sample Challenges
Xiao Xiao, Yu Su, Sijing Zhang +3
Large language models (LLMs) exhibit probabilistic output characteristics, yet conventional evaluation frameworks rely on deterministic scalar metrics. This study introduces a Baye…