SWE-RL by Meta — Reinforcement Learning for Software Engineering LLMs

In this video, we dive into a new Meta research paper: "SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution". This paper introduces SWE-RL, a new reinforcement learning method for real-world software engineering. By training large language models (LLMs) directly on the evolution of real GitHub projects, SWE-RL can empower LLM to be better at software engineering. We break down: • How Meta curated 11 million pull requests from GitHub. • SWE-RL training pipeline. • SWE-RL state-of-the-art results on SWE-bench Verified for open-source models under 100B parameters. 🔗 Written Review: https://aipapersacademy.com/swe-rl/ 🔗 Paper Link: https://arxiv.org/abs/2502.18449 🔗 Code: https://github.com/facebookresearch/swe-rl ___________________ 🔔 Subscribe for more AI paper reviews! 📩 Join the newsletter → https://aipapersacademy.com/newsletter/ Become a patron - https://www.patreon.com/aipapersacademy The video was edited using VideoScribe - https://tidd.ly/44TZEiX ___________________ #airesearch #metaai #swe_rl #reinforcementlearning #llm Chapters: 0:00 Introduction 1:15 GitHub PRs Curation 3:20 SWE-RL Training 5:42 Aha Moments 6:39 SWE-RL Results