Search Results for author: Jonas Gehring

Found 9 papers, 7 papers with code

Code Llama: Open Foundation Models for Code

2 code implementations24 Aug 2023 Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, Gabriel Synnaeve

We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for large input contexts, and zero-shot instruction following ability for programming tasks.

Code Generation Instruction Following

Leveraging Demonstrations with Latent Space Priors

1 code implementation26 Oct 2022 Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause, Gabriel Synnaeve, Nicolas Usunier

Starting with a learned joint latent space, we separately train a generative model of demonstration sequences and an accompanying low-level policy.

Offline RL

Hierarchical Skills for Efficient Exploration

1 code implementation NeurIPS 2021 Jonas Gehring, Gabriel Synnaeve, Andreas Krause, Nicolas Usunier

We alleviate the need for prior knowledge by proposing a hierarchical skill learning framework that acquires skills of varying complexity in an unsupervised manner.

Continuous Control Efficient Exploration +4

Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger

1 code implementation ICLR 2018 Gabriel Synnaeve, Zeming Lin, Jonas Gehring, Dan Gant, Vegard Mella, Vasil Khalidov, Nicolas Carion, Nicolas Usunier

We formulate the problem of defogging as state estimation and future state prediction from previous, partial observations in the context of real-time strategy games.


High-Level Strategy Selection under Partial Observability in StarCraft: Brood War

no code implementations21 Nov 2018 Jonas Gehring, Da Ju, Vegard Mella, Daniel Gant, Nicolas Usunier, Gabriel Synnaeve

We consider the problem of high-level strategy selection in the adversarial setting of real-time strategy games from a reinforcement learning perspective, where taking an action corresponds to switching to the respective strategy.

reinforcement-learning Reinforcement Learning (RL) +2

STARDATA: A StarCraft AI Research Dataset

1 code implementation7 Aug 2017 Zeming Lin, Jonas Gehring, Vasil Khalidov, Gabriel Synnaeve

We provide full game state data along with the original replays that can be viewed in StarCraft.

Imitation Learning Starcraft +1

Cannot find the paper you are looking for? You can Submit a new open access paper.