The open-source GLM-5 model has achieved a record low hallucination rate, utilizing a new reinforcement learning technique known as “slime,” which is designed specifically to minimize such errors in large language models. This innovation highlights the ongoing challenge of reducing hallucinations, a key goal for developers to enhance trust in real-world AI deployments. Open-source projects like GLM-5 are crucial as they encourage community-driven advancements, contributing to improvements in AI reliability and performance.
GLM-5 achieves record low hallucination rate using RL ‘slime’ technique
