A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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This paper surveys the evolution and landscape of large language model evaluation, highlighting challenges in ensuring reliability, fairness, and societal benefit.
Muthukuda Arachchige Dona Shiroma Jeeva Shirajanie Niriella
This paper examines AI's integration into Sri Lankan sentencing, highlighting risks of bias and proposing regulatory frameworks for equitable judicial use.
Kevin B. Johnson, Ivor B. Horn, Eric Horvitz
This Viewpoint discusses the pursuit of fairness and equity in AI in health care to drive transformative changes and reduce health disparities.
Pere Martra, Eugenio Martínez Cámara, Alfonso Ureña López
Fairness Pruning introduces a lightweight structural intervention that locates demographic bias in GLU-MLP layers by zeroing at most 40 neurons, achieving 99.49% capability retention while destabilizing bias bidirectionally.
Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.
A comprehensive survey of bias evaluation and mitigation techniques for LLMs, proposing taxonomies for metrics, datasets, and mitigation methods.
W. Holmes, Kaśka Porayska‐Pomsta, Ken Holstein, et al.
This paper surveys 60 AIED researchers to identify ethical gaps and proposes a multidisciplinary framework for fairness, accountability, transparency, bias, autonomy, agency, and inclusion in AI education.