{"total":15,"rows":[{"id":"2310.00907","title":"The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice","created":"2023-10-02","cited_by_count":87,"area":null},{"id":"2405.19479","title":"Participation in the age of foundation models","created":"2024-05-29","cited_by_count":32,"area":null},{"id":"2409.19430","title":"'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants","created":"2024-09-28","cited_by_count":28,"area":null},{"id":"2312.02798","title":"Weakly Supervised Detection of Hallucinations in LLM Activations","created":"2023-12-05","cited_by_count":20,"area":null},{"id":"2304.10182","title":"Using Text-to-Image Generation for Architectural Design Ideation","created":"2023-04-20","cited_by_count":16,"area":null},{"id":"2407.08867","title":"Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Survey","created":"2024-07-11","cited_by_count":15,"area":null},{"id":"2309.12327","title":"Ground Truth Or Dare: Factors Affecting The Creation Of Medical Datasets For Training AI","created":"2023-08-12","cited_by_count":11,"area":null},{"id":"2404.13060","title":"The Necessity of AI Audit Standards Boards","created":"2024-04-11","cited_by_count":9,"area":null},{"id":"2407.17596","title":"Quality Assured: Rethinking Annotation Strategies in Imaging AI","created":"2024-07-24","cited_by_count":6,"area":null},{"id":"2509.24506","title":"Building Benchmarks from the Ground Up: Community-Centered Evaluation of LLMs in Healthcare Chatbot Settings","created":"2025-09-29","cited_by_count":5,"area":null},{"id":"2307.16787","title":"The Ethics of AI Value Chains","created":"2023-07-31","cited_by_count":3,"area":null},{"id":"2303.01930","title":"A toolkit of dilemmas: Beyond debiasing and fairness formulas for responsible AI/ML","created":"2023-03-03","cited_by_count":2,"area":null},{"id":"2311.18046","title":"Making Data Work Count","created":"2023-11-29","cited_by_count":2,"area":null},{"id":"2602.11318","title":"The Consensus Trap: Dissecting Subjectivity and the \"Ground Truth\" Illusion in Data Annotation","created":"2026-02-11","cited_by_count":2,"area":null},{"id":"2301.09902","title":"Investigating Labeler Bias in Face Annotation for Machine Learning","created":"2023-01-24","cited_by_count":1,"area":null}],"next_cursor":null}