4 citations · 4 across the 3 of their papers we have counts for
3 papers
Retrieval-Augmented Multi-LLM Ensemble for Industrial Part Specification Extraction
Muzakkiruddin Ahmed Mohammed, John R. Talburt, Leon Claasssens +1
Industrial part specification extraction from unstructured text remains a persistent challenge in manufacturing, procurement, and maintenance, where manual processing is both time-…
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…