On First-Order Meta-Learning Algorithms. - Alex Nichol; Joshua Achiam; John Schulman (CoRR, 2018)

Gotta Learn Fast: A New Benchmark for Generalization in RL. - Alex Nichol; Vicki Pfau; Christopher Hesse; Oleg Klimov; John Schulman (CoRR, 2018)

VQ-DRAW: A Sequential Discrete VAE. - Alex Nichol (CoRR, 2020)

Improved Denoising Diffusion Probabilistic Models. - Alexander Quinn Nichol; Prafulla Dhariwal (ICML, 2021)

Diffusion Models Beat GANs on Image Synthesis. - Prafulla Dhariwal; Alexander Quinn Nichol (NeurIPS, 2021)

Evaluating Large Language Models Trained on Code. - Mark Chen 003; Jerry Tworek; Heewoo Jun; Qiming Yuan; Henrique Pondé de Oliveira Pinto; Jared Kaplan; Harri Edwards; Yuri Burda; Nicholas Joseph; Greg Brockman; Alex Ray; Raul Puri; et al. (CoRR, 2021)

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. - Alexander Quinn Nichol; Prafulla Dhariwal; Aditya Ramesh; Pranav Shyam; Pamela Mishkin; Bob McGrew; Ilya Sutskever; Mark Chen 003 (ICML, 2022)

Hierarchical Text-Conditional Image Generation with CLIP Latents. - Aditya Ramesh; Prafulla Dhariwal; Alex Nichol; Casey Chu; Mark Chen 003 (CoRR, 2022)

Point-E: A System for Generating 3D Point Clouds from Complex Prompts. - Alex Nichol; Heewoo Jun; Prafulla Dhariwal; Pamela Mishkin; Mark Chen 003 (CoRR, 2022)

Shap-E: Generating Conditional 3D Implicit Functions. - Heewoo Jun; Alex Nichol (CoRR, 2023)

GPT-4o System Card. - Aaron Hurst; Adam Lerer; Adam P. Goucher; Adam Perelman; Aditya Ramesh; Aidan Clark; AJ Ostrow; Akila Welihinda; Alan Hayes; Alec Radford; Aleksander Madry; Alex Baker-Whitcomb; et al. (CoRR, 2024)