1 citations · 2 across the 6 of their papers we have counts for
6 papers
Wiki-TabNER: Integrating Named Entity Recognition into Wikipedia Tables
Aneta Koleva, Martin Ringsquandl, Ahmed Hatem +2
Interest in solving table interpretation tasks has grown over the years, yet it still relies on existing datasets that may be overly simplified. This is potentially reducing the ef…
Adversarial Attacks on Tables with Entity Swap
Aneta Koleva, Martin Ringsquandl, Volker Tresp
The capabilities of large language models (LLMs) have been successfully applied in the context of table representation learning. The recently proposed tabular language models have…
Active Learning with Tabular Language Models
Martin Ringsquandl, Aneta Koleva
Despite recent advancements in tabular language model research, real-world applications are still challenging. In industry, there is an abundance of tables found in spreadsheets, b…
Named Entity Recognition in Industrial Tables using Tabular Language Models
Aneta Koleva, Martin Ringsquandl, Mark Buckley +2
Specialized transformer-based models for encoding tabular data have gained interest in academia. Although tabular data is omnipresent in industry, applications of table transformer…
Generating Table Vector Representations
Aneta Koleva, Martin Ringsquandl, Mitchell Joblin +1
High-quality Web tables are rich sources of information that can be used to populate Knowledge Graphs (KG). The focus of this paper is an evaluation of methods for table-to-class a…
Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019
Nacira Abbas, Kholoud Alghamdi, Mortaza Alinam +71
One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is…