13 papers · 1 filter
Geospatial Diffusion-based Evolution Synthesis (GeoDES) for Storm-Centered Weather Augmentation
Sonia Cromp, Satya Sai Srinath Namburi GNVV, Youran Wang +4
While machine learning-based weather models hold significant promise, they struggle to predict the detailed structure of large-scale weather systems such as cyclonic storms. Region…
WARP: Weight-Space Analysis for Recovering Training Data Portfolios
Tzu-Heng Huang, Aditya Goyal, John Cooper +1
Foundation models are routinely released to the public, yet the data recipes used to train them -- such as domain mixture weights that determine how different sources are sampled -…
Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights
Tzu-Heng Huang, Manjot Bilkhu, John Cooper +2
Large-scale web-crawled datasets contain noise, bias, and irrelevant information, necessitating data selection techniques. Existing methods depend on hand-crafted heuristics, downs…
Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models
John Cooper, Ilias Diakonikolas, Mingchen Ma +1
Hybrid sequence models--combining Transformer and state-space model layers--seek to gain the expressive versatility of attention as well as the computational efficiency of state-sp…
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…
CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation
Jitian Zhao, Changho Shin, Tzu-Heng Huang +2
LLM-as-a-judge ensembles are the standard paradigm for scalable evaluation, but their aggregation mechanisms suffer from a fundamental flaw: they implicitly assume that judges prov…