1.1k citations
- University of CambridgeGB13 papers
- King's College LondonGB9 papers
- University College LondonGB8 papers
- Politecnico di TorinoIT6 papers
- University of BristolGB6 papers
- IT University of CopenhagenDK3 papers
- University of NottinghamGB3 papers
- University of OxfordGB3 papers
- University of TurinIT3 papers
- Aristotle University of ThessalonikiGR2 papers
- Cancer Research UKGB2 papers
- École Polytechnique Fédérale de LausanneCH2 papers
55 papers
Will AI Agents Free Us From Meaningless Work? A Human-Centered Analysis
Davide Ghia, Jaspreet Ranjit, Tania Cerquitelli +1
Some claim that AI agents will free workers from the boring parts of their jobs, yet little is known about how workers themselves identify which tasks should be automated. Prior re…
Impact Assessment Card: Communicating Risks and Benefits of AI Uses
Edyta Bogucka, Marios Constantinides, Sanja Šćepanović +1
Communicating the risks and benefits of AI is important for regulation and public understanding. Yet current methods such as technical reports often exclude people without technica…
UST-GNN: A Unified Spatial--Topological Graph Neural Network Framework for Urban Analytics--Demonstrated through a Case Study on Urban Health Prediction
Minwei Zhao, Sanja Scepanovic, Stephen Law +3
Understanding how social, demographic, environmental, and spatial factors jointly shape urban outcomes is essential for sustainable urban development and evidence-based policy. Tra…
C3AI: Crafting and Evaluating Constitutions for Constitutional AI
Yara Kyrychenko, Ke Zhou, Edyta Bogucka +1
Constitutional AI (CAI) guides LLM behavior using constitutions, but identifying which principles are most effective for model alignment remains an open challenge. We introduce the…
PRIMUS: Pretraining IMU Encoders with Multimodal Self-Supervision
Arnav M. Das, Chi Ian Tang, Fahim Kawsar +1
Sensing human motions through Inertial Measurement Units (IMUs) embedded in personal devices has enabled significant applications in health and wellness. Labeled IMU data is scarce…
NLPGuard: A Framework for Mitigating the Use of Protected Attributes by NLP Classifiers
Salvatore Greco, Ke Zhou, Licia Capra +2
AI regulations are expected to prohibit machine learning models from using sensitive attributes during training. However, the latest Natural Language Processing (NLP) classifiers,…