14 citations · 16 across the 9 of their papers we have counts for
11 papers
Factual Inconsistencies in Multilingual Wikipedia Tables
Silvia Cappa, Lingxiao Kong, Pille-Riin Peet +3
Wikipedia serves as a globally accessible knowledge source with content in over 300 languages. Despite covering the same topics, the different versions of Wikipedia are written and…
Co-constructing Explanations for AI Systems using Provenance
Jan-Christoph Kalo, Fina Polat, Shubha Guha +1
Modern AI systems are complex workflows containing multiple components and data sources. Data provenance provides the ability to interrogate and potentially explain the outputs of…
Investigating the Robustness of Deductive Reasoning with Large Language Models
Fabian Hoppe, Filip Ilievski, Jan-Christoph Kalo
Large Language Models (LLMs) have been shown to achieve impressive results for many reasoning-based NLP tasks, suggesting a degree of deductive reasoning capability. However, it re…
Semantic Web and Creative AI -- A Technical Report from ISWS 2023
Raia Abu Ahmad, Reham Alharbi, Roberto Barile +74
The International Semantic Web Research School (ISWS) is a week-long intensive program designed to immerse participants in the field. This document reports a collaborative effort p…
ChronoSense: Exploring Temporal Understanding in Large Language Models with Time Intervals of Events
Duygu Sezen Islakoglu, Jan-Christoph Kalo
Large Language Models (LLMs) have achieved remarkable success in various NLP tasks, yet they still face significant challenges in reasoning and arithmetic. Temporal reasoning, a cr…
Evaluating the Knowledge Base Completion Potential of GPT
Blerta Veseli, Simon Razniewski, Jan-Christoph Kalo +1
Structured knowledge bases (KBs) are an asset for search engines and other applications, but are inevitably incomplete. Language models (LMs) have been proposed for unsupervised kn…
Prompt Tuned Embedding Classification for Multi-Label Industry Sector Allocation
Valentin Leonhard Buchner, Lele Cao, Jan-Christoph Kalo +1
Prompt Tuning is emerging as a scalable and cost-effective method to fine-tune Pretrained Language Models (PLMs), which are often referred to as Large Language Models (LLMs). This…
Large Language Models and Knowledge Graphs: Opportunities and Challenges
Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo +13
Large Language Models (LLMs) have taken Knowledge Representation -- and the world -- by storm. This inflection point marks a shift from explicit knowledge representation to a renew…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Prompting as Probing: Using Language Models for Knowledge Base Construction
Dimitrios Alivanistos, Selene Báez Santamaría, Michael Cochez +3
Language Models (LMs) have proven to be useful in various downstream applications, such as summarisation, translation, question answering and text classification. LMs are becoming…
Fast Dual Simulation Processing of Graph Database Queries (Supplement)
Stephan Mennicke, Jan-Christoph Kalo, Denis Nagel +2
Graph database query languages feature expressive, yet computationally expensive pattern matching capabilities. Answering optional query clauses in SPARQL for instance renders the…