68 citations · 92 across the 17 of their papers we have counts for
18 papers
Economies of Open Intelligence: Tracing Power & Participation in the Model Ecosystem
Shayne Longpre, Christopher Akiki, Campbell Lund +6
Since 2019, the Hugging Face Model Hub has been the primary global platform for sharing open weight AI models. By releasing a dataset of the complete history of weekly model downlo…
Generative AI and the Future of the Digital Commons: Five Open Questions and Knowledge Gaps
Arman Noroozian, Lorena Aldana, Marta Arisi +21
The rapid advancement of Generative AI (GenAI) relies heavily on the digital commons, a vast collection of free and open online content that is created, shared, and maintained by c…
INTIMA: A Benchmark for Human-AI Companionship Behavior
Lucie-Aimée Kaffee, Giada Pistilli, Yacine Jernite
AI companionship, where users develop emotional bonds with AI systems, has emerged as a significant pattern with positive but also concerning implications. We introduce Interaction…
Presumed Cultural Identity: How Names Shape LLM Responses
Siddhesh Pawar, Arnav Arora, Lucie-Aimée Kaffee +1
Names are deeply tied to human identity. They can serve as markers of individuality, cultural heritage, and personal history. However, using names as a core indicator of identity c…
Local Differences, Global Lessons: Insights from Organisation Policies for International Legislation
Lucie-Aimée Kaffee, Pepa Atanasova, Anna Rogers
The rapid adoption of AI across diverse domains has led to the development of organisational guidelines that vary significantly, even within the same sector. This paper examines AI…
Wikimedia data for AI: a review of Wikimedia datasets for NLP tasks and AI-assisted editing
Isaac Johnson, Lucie-Aimée Kaffee, Miriam Redi
Wikimedia content is used extensively by the AI community and within the language modeling community in particular. In this paper, we provide a review of the different ways in whic…
Investigating Wit, Creativity, and Detectability of Large Language Models in Domain-Specific Writing Style Adaptation of Reddit's Showerthoughts
Tolga Buz, Benjamin Frost, Nikola Genchev +3
Recent Large Language Models (LLMs) have shown the ability to generate content that is difficult or impossible to distinguish from human writing. We investigate the ability of diff…
Investigating Human Values in Online Communities
Nadav Borenstein, Arnav Arora, Lucie-Aimée Kaffee +1
Studying human values is instrumental for cross-cultural research, enabling a better understanding of preferences and behaviour of society at large and communities therein. To stud…
Coordinated Flaw Disclosure for AI: Beyond Security Vulnerabilities
Sven Cattell, Avijit Ghosh, Lucie-Aimée Kaffee
Harm reporting in Artificial Intelligence (AI) currently lacks a structured process for disclosing and addressing algorithmic flaws, relying largely on an ad-hoc approach. This con…
Why Should This Article Be Deleted? Transparent Stance Detection in Multilingual Wikipedia Editor Discussions
Lucie-Aimée Kaffee, Arnav Arora, Isabelle Augenstein
The moderation of content on online platforms is usually non-transparent. On Wikipedia, however, this discussion is carried out publicly and the editors are encouraged to use the c…
Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing
Lucie-Aimée Kaffee, Arnav Arora, Zeerak Talat +1
Dual use, the intentional, harmful reuse of technology and scientific artefacts, is a problem yet to be well-defined within the context of Natural Language Processing (NLP). Howeve…
TempEL: Linking Dynamically Evolving and Newly Emerging Entities
Klim Zaporojets, Lucie-Aimee Kaffee, Johannes Deleu +3
In our continuously evolving world, entities change over time and new, previously non-existing or unknown, entities appear. We study how this evolutionary scenario impacts the perf…
Probing Pre-Trained Language Models for Cross-Cultural Differences in Values
Arnav Arora, Lucie-Aimée Kaffee, Isabelle Augenstein
Language embeds information about social, cultural, and political values people hold. Prior work has explored social and potentially harmful biases encoded in Pre-Trained Language…
Assessing the quality of sources in Wikidata across languages: a hybrid approach
Gabriel Amaral, Alessandro Piscopo, Lucie-Aimée Kaffee +2
Wikidata is one of the most important sources of structured data on the web, built by a worldwide community of volunteers. As a secondary source, its contents must be backed by cre…
References in Wikipedia: The Editors' Perspective
Lucie-Aimée Kaffee, Hady Elsahar
References are an essential part of Wikipedia. Each statement in Wikipedia should be referenced. In this paper, we explore the creation and collection of references for new Wikiped…
Linked Open Data Validity -- A Technical Report from ISWS 2018
Tayeb Abderrahmani Ghor, Esha Agrawal, Mehwish Alam +68
Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied by a URI and accessible via HTTP. LOD encodes globalscale knowledge potentially a…
Learning to Generate Wikipedia Summaries for Underserved Languages from Wikidata
Lucie-Aimée Kaffee, Hady Elsahar, Pavlos Vougiouklis +4
While Wikipedia exists in 287 languages, its content is unevenly distributed among them. In this work, we investigate the generation of open domain Wikipedia summaries in underserv…
Neural Wikipedian: Generating Textual Summaries from Knowledge Base Triples
Pavlos Vougiouklis, Hady Elsahar, Lucie-Aimée Kaffee +4
Most people do not interact with Semantic Web data directly. Unless they have the expertise to understand the underlying technology, they need textual or visual interfaces to help…