July 7, 2022, 5:18 p.m. | Synced

Synced syncedreview.com

In the new paper CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning, a Salesforce Research team presents CodeRL, a novel framework for program synthesis tasks that employs pretrained language models (LMs) and deep reinforcement learning (RL) and achieves state-of-the-art performance on the challenging APPS benchmark while also demonstrating impressive zero-shot transfer capabilities.


The post Salesforce’s CodeRL Achieves SOTA Code Generation Results With Strong Zero-Shot Transfer Capabilities first appeared on Synced.

ai artificial intelligence code code generation deep-neural-networks generation machine learning machine learning & data science ml pretrained language model research salesforce sota technology transfer

More from syncedreview.com / Synced

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Senior Machine Learning Engineer

@ Samsara | Canada - Remote