3 papers
cs.LG2026
Weight Updates as Activation Shifts: A Principled Framework for Steering
Dyah Adila, John Cooper, Alexander Yun +2
Activation steering promises to be an extremely parameter-efficient form of adaptation, but its effectiveness depends on critical design choices -- such as intervention location an…
cs.LG2025
R&B: Domain Regrouping and Data Mixture Balancing for Efficient Foundation Model Training
Albert Ge, Tzu-Heng Huang, John Cooper +7
Data mixing strategies have successfully reduced the costs involved in training language models. While promising, such methods suffer from two flaws. First, they rely on predetermi…
cs.LG2024
Weak-to-Strong Generalization Through the Data-Centric Lens
Changho Shin, John Cooper, Frederic Sala
The weak-to-strong generalization phenomenon is the driver for important machine learning applications including highly data-efficient learning and, most recently, performing super…