37 citations · 62 across the 9 of their papers we have counts for
10 papers
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…
MCP vs RAG vs NLWeb vs HTML: A Comparison of the Effectiveness and Efficiency of Different Agent Interfaces to the Web (Technical Report)
Aaron Steiner, Ralph Peeters, Christian Bizer
Large language model agents are increasingly used to automate web tasks such as product search, offer comparison, and checkout. Current research explores different interfaces throu…
WebMall -- A Multi-Shop Benchmark for Evaluating Web Agents
Ralph Peeters, Aaron Steiner, Luca Schwarz +2
LLM-based web agents have the potential to automate long-running web tasks, such as searching for products in multiple e-shops and subsequently ordering the cheapest products that…
Fine-tuning Large Language Models for Entity Matching
Aaron Steiner, Ralph Peeters, Christian Bizer
Generative large language models (LLMs) are a promising alternative to pre-trained language models for entity matching due to their high zero-shot performance and ability to genera…
Entity Matching using Large Language Models
Ralph Peeters, Aaron Steiner, Christian Bizer
Entity matching is the task of deciding whether two entity descriptions refer to the same real-world entity. Entity matching is a central step in most data integration pipelines. M…
Using ChatGPT for Entity Matching
Ralph Peeters, Christian Bizer
Entity Matching is the task of deciding if two entity descriptions refer to the same real-world entity. State-of-the-art entity matching methods often rely on fine-tuning Transform…
WDC Products: A Multi-Dimensional Entity Matching Benchmark
Ralph Peeters, Reng Chiz Der, Christian Bizer
The difficulty of an entity matching task depends on a combination of multiple factors such as the amount of corner-case pairs, the fraction of entities in the test set that have n…
Supervised Contrastive Learning for Product Matching
Ralph Peeters, Christian Bizer
Contrastive learning has moved the state of the art for many tasks in computer vision and information retrieval in recent years. This poster is the first work that applies supervis…
Cross-Language Learning for Entity Matching
Ralph Peeters, Christian Bizer
Transformer-based entity matching methods have significantly moved the state of the art for less-structured matching tasks such as matching product offers in e-commerce. In order t…