389 citations · 2.3k across the 27 of their papers we have counts for
27 papers
OpenAI GPT-5 System Card
Aaditya Singh, Adam Fry, Adam Perelman +483
This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reason…
Small-to-Large Generalization: Data Influences Models Consistently Across Scale
Alaa Khaddaj, Logan Engstrom, Aleksander Madry
Choice of training data distribution greatly influences model behavior. Yet, in large-scale settings, precisely characterizing how changes in training data affects predictions is o…
DataMIL: Selecting Data for Robot Imitation Learning with Datamodels
Shivin Dass, Alaa Khaddaj, Logan Engstrom +3
Recently, the robotics community has amassed ever larger and more diverse datasets to train generalist policies. However, while these policies achieve strong mean performance acros…
MAGIC: Near-Optimal Data Attribution for Deep Learning
Andrew Ilyas, Logan Engstrom
The goal of predictive data attribution is to estimate how adding or removing a given set of training datapoints will affect model predictions. In convex settings, this goal is str…
Optimizing ML Training with Metagradient Descent
Logan Engstrom, Andrew Ilyas, Benjamin Chen +3
A major challenge in training large-scale machine learning models is configuring the training process to maximize model performance, i.e., finding the best training setup from a va…
DsDm: Model-Aware Dataset Selection with Datamodels
Logan Engstrom, Axel Feldmann, Aleksander Madry
When selecting data for training large-scale models, standard practice is to filter for examples that match human notions of data quality. Such filtering yields qualitatively clean…