Groupe Sequence Policy Optimization

Arxiv: https://www.arxiv.org/abs/2507.18071

This episode of "The AI Research Deep Dive" unpacks "Group Sequence Policy Optimization" (GSPO), a new and powerful reinforcement learning algorithm from the creators of the Qwen models. The host explains how GSPO solves the critical problem of training instability and "model collapse" that plagues large-scale AI development. Listeners will learn the paper's core insight: a subtle but fundamental flaw in previous methods that applied sentence-level rewards to individual words, creating a noisy and unstable learning signal. The episode details GSPO's elegant solution of aligning the optimization with the reward by using a single, stable importance weight for the entire generated sequence, a change that not only improves stability and performance but also radically simplifies the training of massive Mixture of Experts (MoE) models.