Gehring, Jonas

Convolutional Sequence to Sequence Learning

Gehring, J., Auli, M., Grangier, D., Yarats, D., & Dauphin, Y. N. (2017) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 2,850

Code Llama: Open Foundation Models for Code

Rozière, B., Gehring, J., Gloeckle, F., Sootla, S., Gat, I., Tan, X. E., Adi, Y., Liu, J., Sauvestre, R., Remez, T., et al. (2023) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 531

RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning

Gehring, J., Zheng, K., Copet, J., Mella, V., Carbonneaux, Q., Cohen, T., & Synnaeve, G. (2024) · arXiv

Software Engineering ResearchTeaching and Learning Programming

Cited by 23

The Larger the Better? Improved LLM Code-Generation via Budget Reallocation

Hassid, M., Remez, T., Gehring, J., Schwartz, R., & Adi, Y. (2024) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 6

CWM: An Open-Weights LLM for Research on Code Generation with World Models

FAIR CodeGen team, Copet, J., Carbonneaux, Q., Cohen, G., Gehring, J., Kahn, J., Kossen, J., Kreuk, F., McMilin, E., Meyer, M., et al. (2025) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 0