GLM-5 advances foundation models with DSA for cost reduction, asynchronous reinforcement learning for improved alignment, and enhanced coding capabilities for real-world software engineering.
STATe presents an interpretable inference-time compute method that uses discrete textual interventions to generate diverse, high-quality, and explainable text by searching over reasoning patterns rather than relying on stochastic sampling.