From the 2 of 5 linked papers with an AI index.
5 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…
Bridging Compute- and Data-Optimal Pretraining
Tian Qin, Kimia Hamidieh, David Alvarez-Melis
The paper introduces Compute-Data (CD) scaling laws that unify compute-optimal and data-optimal pretraining regimes by modeling the effectiveness of derived tokens, and shows how t…
Domain-Aware Scaling Laws Uncover Data Synergy
Kimia Hamidieh, Lester Mackey, David Alvarez-Melis
The paper defines and measures how mixing data from different domains during language model pretraining can produce synergistic or interfering effects, and shows that accounting fo…
Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification
Kimia Hamidieh, Veronika Thost, Walter Gerych +2
Large language models (LLMs) often produce confident yet incorrect responses, and uncertainty quantification is one potential solution to more robust usage. Recent works routinely…
Selective Prediction via Training Dynamics
Stephan Rabanser, Anvith Thudi, Kimia Hamidieh +5
Selective Prediction is the task of rejecting inputs a model would predict incorrectly on. This involves a trade-off between input space coverage (how many data points are accepted…