research
∙
09/15/2023
Adversarial Attacks on Tables with Entity Swap
The capabilities of large language models (LLMs) have been successfully ...
share
research
∙
11/08/2022
Active Learning with Tabular Language Models
Despite recent advancements in tabular language model research, real-wor...
research
∙
09/29/2022
Named Entity Recognition in Industrial Tables using Tabular Language Models
Specialized transformer-based models for encoding tabular data have gain...
research
∙
12/03/2021
Combining Sub-Symbolic and Symbolic Methods for Explainability
Similarly to other connectionist models, Graph Neural Networks (GNNs) la...
research
∙
11/25/2021
Demystifying Graph Neural Network Explanations
Graph neural networks (GNNs) are quickly becoming the standard approach ...
research
∙
10/28/2021
Generating Table Vector Representations
High-quality Web tables are rich sources of information that can be used...
research
∙
09/08/2021
On Event-Driven Knowledge Graph Completion in Digital Factories
Smart factories are equipped with machines that can sense their manufact...
research
∙
09/08/2021
Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids
The application of graph neural networks (GNNs) to the domain of electri...
research
∙
03/18/2021
Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs
Biomedical knowledge graphs permit an integrative computational approach...
research
∙
07/10/2020
Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing
The graph structure of biomedical data differs from those in typical kno...
research
∙
01/09/2020
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs
We propose a novel method for fact-checking on knowledge graphs based on...
research
∙
01/02/2020