47 citations · 68 across the 6 of their papers we have counts for
8 papers
How Much Is an AI Token Worth? Scaling Laws for Wild AI-Generated Web Text
Jenna Russell, Ben Glickenhaus, Katherine Thai +4
Web text makes up the majority of pretraining data and is increasingly AI-generated. After applying FineWeb quality filtering, we find that 27.5% of tokens from June 2026 web data…
Pangram 4 Technical Report
Ben Glickenhaus, Katherine Thai, Jenna Russell +4
We present Pangram 4, the latest deep-learning-based AI-text classification model from Pangram Labs. We achieve an AUROC of 0.9916 with a false positive rate of 0.0041% and a false…
EditLens: Quantifying the Extent of AI Editing in Text
Katherine Thai, Bradley Emi, Elyas Masrour +1
A significant proportion of queries to large language models ask them to edit user-provided text, rather than generate new text from scratch. While previous work focuses on detecti…
AI use in American newspapers is widespread, uneven, and rarely disclosed
Jenna Russell, Marzena Karpinska, Destiny Akinode +4
AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K arti…
DAMAGE: Detecting Adversarially Modified AI Generated Text
Elyas Masrour, Bradley Emi, Max Spero
AI humanizers are a new class of online software tools meant to paraphrase and rewrite AI-generated text in a way that allows them to evade AI detection software. We study 19 AI hu…
Technical Report on the Pangram AI-Generated Text Classifier
Bradley Emi, Max Spero
We present Pangram Text, a transformer-based neural network trained to distinguish text written by large language models from text written by humans. Pangram Text outperforms zero-…
Learning to Navigate Using Mid-Level Visual Priors
Alexander Sax, Jeffrey O. Zhang, Bradley Emi +4
How much does having visual priors about the world (e.g. the fact that the world is 3D) assist in learning to perform downstream motor tasks (e.g. navigating a complex environment)…
Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies
Alexander Sax, Bradley Emi, Amir R. Zamir +3
How much does having visual priors about the world (e.g. the fact that the world is 3D) assist in learning to perform downstream motor tasks (e.g. delivering a package)? We study t…