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20212026
most citedSupervised Contrastive Learning for Product Matching

37 citations · 62 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024★ 2 cited

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…

cs.CL2023★ 9 cited

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…

cs.CL2023★ 3 cited

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…

cs.CL2021★ 5 cited

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…