4 citations · 10 across the 8 of their papers we have counts for
9 papers
Narrowing the Horizon: Quantifying Topic Saliency Shifts in Generative Monoculture
Oriane Peter, Elena Simperl, Kate Devlin
As Large Language Models (LLMs) become central to how we access and share information, they play an increasingly powerful role in shaping global knowledge. However, as these models…
The CitizenQuery Benchmark: A Novel Dataset and Evaluation Pipeline for Measuring LLM Performance in Citizen Query Tasks
Neil Majithia, Rajat Shinde, Zo Chapman +5
"Citizen queries" are questions asked by an individual about government policies, guidance, and services that are relevant to their circumstances, encompassing a range of topics in…
Keywords are not always the key: A metadata field analysis for natural language search on open data portals
Lisa-Yao Gan, Arunav Das, Johanna Walker +1
Open data portals are essential for providing public access to open datasets. However, their search interfaces typically rely on keyword-based mechanisms and a narrow set of metada…
Methods to Assess the UK Government's Current Role as a Data Provider for AI
Neil Majithia, Elena Simperl
Governments typically collect and steward a vast amount of high-quality data on their citizens and institutions, and the UK government is exploring how it can better publish and pr…
AI data transparency: an exploration through the lens of AI incidents
Sophia Worth, Ben Snaith, Arunav Das +2
Knowing more about the data used to build AI systems is critical for allowing different stakeholders to play their part in ensuring responsible and appropriate deployment and use.…
Knowledge Prompting: How Knowledge Engineers Use Large Language Models
Elisavet Koutsiana, Johanna Walker, Michelle Nwachukwu +3
Despite many advances in knowledge engineering (KE), challenges remain in areas such as engineering knowledge graphs (KGs) at scale, keeping up with evolving domain knowledge, mult…
A Comparative Analysis of Conversational Large Language Models in Knowledge-Based Text Generation
Phillip Schneider, Manuel Klettner, Elena Simperl +1
Generating natural language text from graph-structured data is essential for conversational information seeking. Semantic triples derived from knowledge graphs can serve as a valua…
Evaluating Large Language Models in Semantic Parsing for Conversational Question Answering over Knowledge Graphs
Phillip Schneider, Manuel Klettner, Kristiina Jokinen +2
Conversational question answering systems often rely on semantic parsing to enable interactive information retrieval, which involves the generation of structured database queries f…
Prompting Datasets: Data Discovery with Conversational Agents
Johanna Walker, Elisavet Koutsiana, Joe Massey +2
Can large language models assist in data discovery? Data discovery predominantly happens via search on a data portal or the web, followed by assessment of the dataset to ensure it…