4 citations · 4 across the 1 of their papers we have counts for
3 papers
Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency
Matthew L. Smith, Jonathan P. Shock, Samuel T. Segun +2
While scaling laws govern aggregate large language model performance, no scaling law has linked factual recall to both model size and training-data composition. We evaluated 38 mod…
AI for a Planet Under Pressure
Victor Galaz, Maria Schewenius, Jonathan F. Donges +26
Artificial intelligence (AI) is already driving scientific breakthroughs in a variety of research fields, ranging from the life sciences to mathematics. This raises a critical ques…
Toward an African Agenda for AI Safety
Samuel T. Segun, Rachel Adams, Ana Florido +22
This paper maps Africa's distinctive AI risk profile, from deepfake fuelled electoral interference and data colonial dependency to compute scarcity, labour disruption and dispropor…