4 citations · 5 across the 3 of their papers we have counts for
3 papers
Leveraging large language models for efficient representation learning for entity resolution
Xiaowei Xu, Bi T. Foua, Xingqiao Wang +2
In this paper, the authors propose TriBERTa, a supervised entity resolution system that utilizes a pre-trained large language model and a triplet loss function to learn representat…
Towards Trustable Language Models: Investigating Information Quality of Large Language Models
Rick Rejeleene, Xiaowei Xu, John Talburt
Large language models (LLM) are generating information at a rapid pace, requiring users to increasingly rely and trust the data. Despite remarkable advances of LLM, Information gen…
Graph-based hierarchical record clustering for unsupervised entity resolution
Islam Akef Ebeid, John R. Talburt, Md Abdus Salam Siddique
Here we study the problem of matched record clustering in unsupervised entity resolution. We build upon a state-of-the-art probabilistic framework named the Data Washing Machine (D…