6 papers
MatrAIx: Simulating the World with 8.3 Billion Persona Agents
Xiaomin Li, Yuexing Hao, Jianheng Hou +90
Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…
Training and Evaluating Diffusion Policies with Long Context Lengths
Abhinav Agarwal, Adam Wei, Taylan Kargin +6
Imitation learning has enabled highly-dexterous robotic manipulation from RGB observations. Policies trained with these methods, however, typically condition robot actions on only…
Spectral Scaling Laws of Muon
Gagik Magakyan, Pablo Parrilo, Asuman Ozdaglar
Orthonormalized update rules have rapidly become a leading choice of optimizer for training large language models, with recent open-source state-of-the-art models adopting Muon. To…
How AI Aggregation Affects Knowledge
Daron Acemoglu, Tianyi Lin, Asuman Ozdaglar +1
Artificial intelligence (AI) changes social learning when aggregated outputs become training data for future predictions. To study this, we extend the DeGroot model by introducing…
A Bayesian Framework for Human-AI Collaboration: Complementarity and Correlation Neglect
Saurabh Amin, Amine Bennouna, Daniel Huttenlocher +3
We develop a decision-theoretic model of human-AI interaction to study when AI assistance improves or impairs human decision-making. A human decision-maker observes private informa…
Wikipedia Contributions in the Wake of ChatGPT
Liang Lyu, James Siderius, Hannah Li +3
How has Wikipedia activity changed for articles with content similar to ChatGPT following its introduction? We estimate the impact using differences-in-differences models, with dis…