Topic: company:openai-research

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1. Language Models are Few-Shot Learners

   Paper • May 28, 2020 • arXiv • Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei

   Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. While typically task-agnostic i...

2. Generative Pretraining from Pixels

   Paper • Jun 17, 2020 • OpenAI • Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun, David Luan, Ilya Sutskever

   Inspired by the success of unsupervised representation learning in natural language processing with models like GPT-2, we examine whether similar models can learn useful representations for images....

3. Jukebox: A Generative Model for Music

   Paper • Apr 30, 2020 • arXiv • Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, Ilya Sutskever

   We introduce Jukebox, a generative model that produces high-fidelity, highly diverse music with singing in the raw audio domain. We model music as a sequence of discrete tokens by using a multi-sca...

4. OpenAI o1 System Card

   Paper • Sep 12, 2024 • OpenAI • OpenAI

   We introduce OpenAI o1, a new series of large language models trained with reinforcement learning to perform complex reasoning. o1 models are designed to spend more time thinking before they respon...

5. Point-E: A System for Generating 3D Point Clouds from Complex Prompts

   Paper • Dec 16, 2022 • arXiv • Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, Mark Chen

   While text-to-image generation has witnessed rapid progress, text-to-3D synthesis remains challenging due to the lack of massive 3D datasets and the complexity of 3D representations. We introduce P...

6. Trust Region Policy Optimization

   Paper • Feb 19, 2015 • arXiv • John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, Philipp Moritz

   We describe an iterative procedure for optimizing policies, with guaranteed monotonic improvement. By making several approximations to the theoretically-justified procedure, we develop a practical ...

7. GPT-4 Technical Report

   Paper • Mar 15, 2023 • arXiv • OpenAI

   We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-world scenarios, GPT...

8. Training language models to follow instructions with human feedback

   Paper • Mar 4, 2022 • arXiv • Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, Ryan Lowe

   Making language models bigger does not inherently make them better at following a user's intent. For example, large language models can generate outputs that are untruthful, toxic, or simply not he...

9. OpenAI Gym

   Paper • Jun 5, 2016 • arxiv.org • Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, Wojciech Zaremba

   OpenAI Gym is a toolkit for reinforcement learning research. It includes a growing collection of benchmark problems that expose a common interface, and a website where people can share their result...

10. Evolution Strategies as a Scalable Alternative to Reinforcement Learning

    Paper • Mar 10, 2017 • arxiv.org • Tim Salimans, Jonathan Ho, Xi Chen, Ilya Sutskever

    We explore the use of Evolution Strategies, a class of black box optimization algorithms, as an alternative to popular RL techniques such as Q-learning and Policy Gradients. Experiments on MuJoCo a...