2 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
Entity Matching using Decision Models
Aaron Steiner, Ralph Peeters, Christian Bizer
Entity matching is the task of deciding whether two records describe the same real-world entity. Current entity matching methods rely on pre-trained language models (PLMs) which re…
Billiger.de Products: A Bilingual Entity Matching Benchmark
Aaron Steiner, Ksenia Elagin, Ralph Peeters +2
Existing product matching benchmarks primarily contain English-language product data and are often dominated by a single product category, such as electronics. This paper introduce…
MaDI-Bench: An End-to-End Data Integration Benchmark
Aaron Steiner, Ralph Peeters, Christian Bizer
Data integration is the process of combining data from multiple, heterogeneous sources into a consistent, unified representation. Data integration involves a sequence of interdepen…
Labeling Training Data for Entity Matching Using Large Language Models
Aaron Steiner, Christian Bizer
Large language models (LLMs) achieve strong entity matching performance without task-specific training data, but applying them to large sets of candidate pairs is slow and costly.…
Automatic End-to-End Data Integration using Large Language Models
Aaron Steiner, Christian Bizer
Designing data integration pipelines typically requires substantial manual effort from data engineers to configure pipeline components and label training data. While LLMs have show…