Search Results for author: Johannes Hoffart

Found 18 papers, 8 papers with code

SALT: Sales Autocompletion Linked Business Tables Dataset

1 code implementation6 Jan 2025 Tassilo Klein, Clemens Biehl, Margarida Costa, Andre Sres, Jonas Kolk, Johannes Hoffart

Foundation models, particularly those that incorporate Transformer architectures, have demonstrated exceptional performance in domains such as natural language processing and image processing.

ERP Representation Learning

PORTAL: Scalable Tabular Foundation Models via Content-Specific Tokenization

1 code implementation17 Oct 2024 Marco Spinaci, Marek Polewczyk, Johannes Hoffart, Markus C. Kohler, Sam Thelin, Tassilo Klein

Self-supervised learning on tabular data seeks to apply advances from natural language and image domains to the diverse domain of tables.

Self-Supervised Learning

Large Process Models: A Vision for Business Process Management in the Age of Generative AI

no code implementations2 Sep 2023 Timotheus Kampik, Christian Warmuth, Adrian Rebmann, Ron Agam, Lukas N. P. Egger, Andreas Gerber, Johannes Hoffart, Jonas Kolk, Philipp Herzig, Gero Decker, Han van der Aa, Artem Polyvyanyy, Stefanie Rinderle-Ma, Ingo Weber, Matthias Weidlich

The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a proof-point of the challenges that purely statistics-based approaches have in terms of safety and trustworthiness.

Management

Can Persistent Homology provide an efficient alternative for Evaluation of Knowledge Graph Completion Methods?

1 code implementation30 Jan 2023 Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Johannes Hoffart, Toyotaro Suzumura, Manish Singh

$\mathcal{KP}$ addresses this by representing the topology of the KG completion methods through the lens of topological data analysis, concretely using persistent homology.

Knowledge Graph Completion Topological Data Analysis

HopfE: Knowledge Graph Representation Learning using Inverse Hopf Fibrations

1 code implementation12 Aug 2021 Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Saeedeh Shekarpour, Isaiah Onando Mulang, Johannes Hoffart

A few KGE techniques address interpretability, i. e., mapping the connectivity patterns of the relations (i. e., symmetric/asymmetric, inverse, and composition) to a geometric interpretation such as rotations.

Knowledge Graph Embedding Link Prediction +1

RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network

1 code implementation18 Sep 2020 Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Isaiah Onando Mulang', Saeedeh Shekarpour, Johannes Hoffart, Manohar Kaul

In this paper, we present a novel method named RECON, that automatically identifies relations in a sentence (sentential relation extraction) and aligns to a knowledge graph (KG).

Graph Neural Network Relation +2

Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models

1 code implementation12 Aug 2020 Isaiah Onando Mulang', Kuldeep Singh, Chaitali Prabhu, Abhishek Nadgeri, Johannes Hoffart, Jens Lehmann

We further hypothesize that our proposed KG context can be standardized for Wikipedia, and we evaluate the impact of KG context on state-of-the-art NED model for the Wikipedia knowledge base.

Entity Disambiguation

Robust Disambiguation of Named Entities in Text

no code implementations1 Jul 2011 Johannes Hoffart, Mohamed Amir Yosef, Ilaria Bordino, Hagen Fürstenau, Manfred Pinkal, Marc Spaniol, Bilyana Taneva, Stefan Thater, Gerhard Weikum

Disambiguating named entities in naturallanguage text maps mentions of ambiguous names onto canonical entities like people or places, registered in a knowledge base such as DBpedia or YAGO.

Entity Disambiguation Entity Linking

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