Collaborative Storytelling with Large-scale Neural Language Models. - Eric Nichols; Leo Gao; Randy Gomez (MIG, 2020)

Collaborative Storytelling with Social Robots. - Eric Nichols; Leo Gao; Yurii Vasylkiv; Randy Gomez (IROS, 2021)

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)

An Empirical Exploration in Quality Filtering of Text Data. - Leo Gao (CoRR, 2021)

Cut the CARP: Fishing for zero-shot story evaluation. - Shahbuland Matiana; J. R. Smith; Ryan Teehan; Louis Castricato; Stella Biderman; Leo Gao; Spencer Frazier (CoRR, 2021)

Multitask Prompted Training Enables Zero-Shot Task Generalization. - Victor Sanh; Albert Webson; Colin Raffel; Stephen H. Bach; Lintang Sutawika; Zaid Alyafeai; Antoine Chaffin; Arnaud Stiegler; Teven Le Scao; Arun Raja; Manan Dey; M. Saiful Bari; et al. (CoRR, 2021)

Design and Analysis of a Collaborative Story Generation Game for Social Robots. - Eric Nichols; Leo Gao; Yurii Vasylkiv; Randy Gomez (Frontiers Comput. Sci., 2021)

Multitask Prompted Training Enables Zero-Shot Task Generalization. - Victor Sanh; Albert Webson; Colin Raffel; Stephen H. Bach; Lintang Sutawika; Zaid Alyafeai; Antoine Chaffin; Arnaud Stiegler; Arun Raja; Manan Dey; M Saiful Bari; Canwen Xu; et al. (ICLR, 2022)

Datasheet for the Pile. - Stella Biderman; Kieran Bicheno; Leo Gao (CoRR, 2022)

GPT-NeoX-20B: An Open-Source Autoregressive Language Model. - Sid Black; Stella Biderman; Eric Hallahan; Quentin Anthony; Leo Gao; Laurence Golding; Horace He; Connor Leahy; Kyle McDonell; Jason Phang; Michael Pieler; USVSN Sai Prashanth; et al. (CoRR, 2022)

EleutherAI: Going Beyond "Open Science" to "Science in the Open". - Jason Phang; Herbie Bradley; Leo Gao; Louis Castricato; Stella Biderman (CoRR, 2022)

Scaling Laws for Reward Model Overoptimization. - Leo Gao; John Schulman; Jacob Hilton (ICML, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision. - Collin Burns; Pavel Izmailov; Jan Hendrik Kirchner; Bowen Baker; Leo Gao; Leopold Aschenbrenner; Yining Chen; Adrien Ecoffet; Manas Joglekar; Jan Leike; Ilya Sutskever; Jeffrey Wu 003 (ICML, 2024)

Lessons from the Trenches on Reproducible Evaluation of Language Models. - Stella Biderman; Hailey Schoelkopf; Lintang Sutawika; Leo Gao; Jonathan Tow; Baber Abbasi; Alham Fikri Aji; Pawan Sasanka Ammanamanchi; Sidney Black; Jordan Clive; Anthony DiPofi; Julen Etxaniz; et al. (CoRR, 2024)

Scaling and evaluating sparse autoencoders. - Leo Gao; Tom Dupré la Tour; Henk Tillman; Gabriel Goh; Rajan Troll; Alec Radford; Ilya Sutskever; Jan Leike; Jeffrey Wu 003 (ICLR, 2025)

Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation. - Bowen Baker; Joost Huizinga; Leo Gao; Zehao Dou; Melody Y. Guan; Aleksander Madry; Wojciech Zaremba; Jakub Pachocki; David Farhi (CoRR, 2025)