Llm Rl Visualized
LLM-RL-Visualized is an open-source GitHub repository offering over 100 original SVG diagrams that visually explain core concepts and architectures related to large language models (LLMs), vision-language models (VLMs), reinforcement learning (RL), and associated training algorithms such as RLHF, GRPO, DPO, and SFT. The diagrams include detailed illustrations of processes like online RL with policy-environment interactions, policy-based optimization methods, multi-agent value networks, and token-level reward modeling in LLMs. The use of SVG format allows infinite scaling and selectable text, facilitating in-depth study of complex model components and training dynamics.
An open-source collection of over 100 scalable diagrams illustrating LLM, VLM, and RL principles and training algorithms.
Educational Resource for Researchers and Developers
Users studying large language models and reinforcement learning algorithms can utilize the diagrams to better understand complex architectures and training methods.
Reference for Training Algorithm Design
Practitioners designing or analyzing RL-based training pipelines can reference the visualized processes such as PPO updates and policy optimization.