Let's Verify Step by Step

3 code implementations • Preprint 2023 • Hunter Lightman, Vineet Kosaraju, Yura Burda, Harri Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, Karl Cobbe

We conduct our own investigation, finding that process supervision significantly outperforms outcome supervision for training models to solve problems from the challenging MATH dataset.

Active Learning Math +2

WebGPT: Browser-assisted question-answering with human feedback

2 code implementations • 17 Dec 2021 • Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, John Schulman

This model's answers are preferred by humans 56% of the time to those of our human demonstrators, and 69% of the time to the highest-voted answer from Reddit.

Imitation Learning Navigate +1

Training Verifiers to Solve Math Word Problems

4 code implementations • 27 Oct 2021 • Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, John Schulman

State-of-the-art language models can match human performance on many tasks, but they still struggle to robustly perform multi-step mathematical reasoning.

GSM8K Math +1

Asymmetric self-play for automatic goal discovery in robotic manipulation

no code implementations • 13 Jan 2021 • OpenAI OpenAI, Matthias Plappert, Raul Sampedro, Tao Xu, Ilge Akkaya, Vineet Kosaraju, Peter Welinder, Ruben D'Sa, Arthur Petron, Henrique Ponde de Oliveira Pinto, Alex Paino, Hyeonwoo Noh, Lilian Weng, Qiming Yuan, Casey Chu, Wojciech Zaremba

We train a single, goal-conditioned policy that can solve many robotic manipulation tasks, including tasks with previously unseen goals and objects.

BERT Learns (and Teaches) Chemistry

no code implementations • 11 Jul 2020 • Josh Payne, Mario Srouji, Dian Ang Yap, Vineet Kosaraju

Modern computational organic chemistry is becoming increasingly data-driven.

Drug Discovery

Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks

no code implementations • NeurIPS 2019 • Vineet Kosaraju, Amir Sadeghian, Roberto Martín-Martín, Ian Reid, S. Hamid Rezatofighi, Silvio Savarese

This problem is compounded by the presence of social interactions between humans and their physical interactions with the scene.

Autonomous Vehicles Decoder +3

SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints

1 code implementation • CVPR 2019 • Amir Sadeghian, Vineet Kosaraju, Ali Sadeghian, Noriaki Hirose, S. Hamid Rezatofighi, Silvio Savarese

Whereas, the social attention component aggregates information across the different agent interactions and extracts the most important trajectory information from the surrounding neighbors.

Generative Adversarial Network Self-Driving Cars +1