16 papers
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 -…
Codifying the Judge: Scalable Evaluation via Program Distillation
Tzu-Heng Huang, Shengqi Qiu, Frederic Sala
LLM-as-a-judge has become the standard for automated evaluation, but it suffers from high cost, significant latency, and opaque decisions -- limitations that undermine its scalabil…
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…
RubiCap: Rubric-Guided Reinforcement Learning for Dense Image Captioning
Tzu-Heng Huang, Sirajul Salekin, Javier Movellan +2
Dense image captioning is critical for cross-modal alignment in vision-language pretraining and text-to-image generation, but scaling expert-quality annotations is prohibitively ex…
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…