LLMAR: A Tuning-Free Recommendation Framework for Sparse and Text-Rich Industrial Domains
arXiv:2604.16379v1 Announce Type: cross
Abstract: Industrial B2B applications (e.g., construction site risk prediction, material procurement) face extreme data sparsity yet feature rich textual interactions. In such environments, traditional ID-based …