The Pile: An 800GB Dataset of Diverse Text for Language Modeling. - Leo Gao; Stella Biderman; Sid Black; Laurence Golding; Travis Hoppe; Charles Foster; Jason Phang; Horace He; Anish Thite; Noa Nabeshima; Shawn Presser; Connor Leahy (CoRR, 2021)

Adversarial training for high-stakes reliability. - Daniel M. Ziegler; Seraphina Nix; Lawrence Chan; Tim Bauman; Peter Schmidt-Nielsen; Tao Lin; Adam Scherlis; Noa Nabeshima; Ben Weinstein-Raun; Daniel de Haas; Buck Shlegeris; Nate Thomas (NeurIPS, 2022)

Learning Multi-Level Features with Matryoshka Sparse Autoencoders. - Bart Bussmann; Noa Nabeshima; Adam Karvonen; Neel Nanda (CoRR, 2025)

Parameterized Synthetic Text Generation with SimpleStories. - Lennart Finke; Thomas Dooms; Mat Allen; Juan Diego Rodriguez; Noa Nabeshima; Dan Braun (CoRR, 2025)