18 citations · 35 across the 17 of their papers we have counts for
19 papers
The Evolution of Coordination in a Collective Intelligence System: 25 Years of English Wikipedia and the Emergence of Generative AI
Neal Reeves, Maja Świeczkowska, Amy Rechkemmer +1
English Wikipedia is one of the largest examples of collective intelligence on the Web, sustained not only by article production but also by volunteer coordination and governance.…
Less Is More? When Dataset Context Hurts LLM-Generated Dataset Descriptions
Lisa-Yao Gan, Arunav Das, Johanna Walker +2
Dataset search and reuse are strongly constrained by the quality of metadata such as natural language descriptions, which are often sparse or inconsistent. Although large language…
Multilingual and Cross-Lingual Citation Needed Detection on Wikipedia for Lower-Resource Languages
Gerrit Quaremba, Amy Rechkemmer, Elizabeth Black +2
In automated fact-checking (AFC), check-worthiness detection identifies claims requiring verification based on domain-specific criteria. On Wikipedia, this task instantiates as Cit…
TSM-Bench: Detecting LLM-Generated Text in Real-World Wikipedia Editing Practices
Gerrit Quaremba, Elizabeth Black, Denny Vrandečić +1
Automatically detecting machine-generated text (MGT) is critical to maintaining the knowledge integrity of user-generated content (UGC) platforms such as Wikipedia. Existing detect…
Design Guidance Towards Addressing Over-Reliance on AI in Sensemaking
Yihang Zhao, Wenxin Zhang, Amy Rechkemmer +2
Sensemaking in collaborative work and learning is increasingly supported by GenAI systems, however, emerging evidence suggests that poorly designed GenAI systems tend to provide ex…
Exploring the Design of GenAI-Based Systems to Support Socially Shared Metacognition
Yihang Zhao, Wenxin Zhang, Amy Rechkemmer +2
Socially shared metacognition (SSM) refers to the collective monitoring and regulation of joint cognitive processes in collaborative problem-solving, and is essential for effective…
Machines in the Margins: A Systematic Review of Automated Content Generation for Wikipedia
Neal Reeves, Elena Simperl
Wikipedia is among the largest examples of collective intelligence on the Web with over 61 million articles covering over 320 languages. Although edited and maintained by an active…
Filling in the Blanks? A Systematic Review and Theoretical Conceptualisation for Measuring WikiData Content Gaps
Marisa Ripoll, Neal Reeves, Anelia Kurteva +3
Wikidata is a collaborative knowledge graph which provides machine-readable structured data for Wikimedia projects including Wikipedia. Managed by a community of volunteers, it has…
Schema Generation for Large Knowledge Graphs Using Large Language Models
Bohui Zhang, Yuan He, Lydia Pintscher +2
Schemas play a vital role in ensuring data quality and supporting usability in the Semantic Web and natural language processing. Traditionally, their creation demands substantial i…
PathE: Leveraging Entity-Agnostic Paths for Parameter-Efficient Knowledge Graph Embeddings
Ioannis Reklos, Jacopo de Berardinis, Elena Simperl +1
Knowledge Graphs (KGs) store human knowledge in the form of entities (nodes) and relations, and are used extensively in various applications. KG embeddings are an effective approac…
How an AI-ready National Data Library would help UK science
Albert Meroño-Peñuela, Joe Massey, Andrew Newman +1
In this paper, we provide a technical vision for key enabling elements for the architecture of the UK National Data Library (NDL) with a strong focus on building it as an AI-ready…
Improving Ontology Requirements Engineering with OntoChat and Participatory Prompting
Yihang Zhao, Bohui Zhang, Xi Hu +6
Past ontology requirements engineering (ORE) has primarily relied on manual methods, such as interviews and collaborative forums, to gather user requirements from domain experts, e…
Talking Wikidata: Communication patterns and their impact on community engagement in collaborative knowledge graphs
Elisavet Koutsiana, Ioannis Reklos, Kholoud Saad Alghamdi +3
We study collaboration patterns of Wikidata, one of the world's largest open source collaborative knowledge graph (KG) communities. Collaborative KG communities, play a key role in…
A Standardized Machine-readable Dataset Documentation Format for Responsible AI
Nitisha Jain, Mubashara Akhtar, Joan Giner-Miguelez +15
Data is critical to advancing AI technologies, yet its quality and documentation remain significant challenges, leading to adverse downstream effects (e.g., potential biases) in AI…
Exploring the Impact of ChatGPT on Wikipedia Engagement
Neal Reeves, Wenjie Yin, Elena Simperl
Wikipedia is one of the most popular websites in the world, serving as a major source of information and learning resource for millions of users worldwide. While motivations for it…
Croissant: A Metadata Format for ML-Ready Datasets
Mubashara Akhtar, Omar Benjelloun, Costanza Conforti +28
Data is a critical resource for machine learning (ML), yet working with data remains a key friction point. This paper introduces Croissant, a metadata format for datasets that crea…
User Experience In Dataset Search
Yihang Zhao, Albert Meroño-Peñuela, Elena Simperl
This research investigates User Experience (UX) issues in dataset search, targeting Google Dataset Search and data.europa.eu. It focuses on 6 areas within UX: Initial Interaction,…
Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data
Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta +3
Numbers are crucial for various real-world domains such as finance, economics, and science. Thus, understanding and reasoning with numbers are essential skills for language models…
ChartCheck: Explainable Fact-Checking over Real-World Chart Images
Mubashara Akhtar, Nikesh Subedi, Vivek Gupta +3
Whilst fact verification has attracted substantial interest in the natural language processing community, verifying misinforming statements against data visualizations such as char…