GRACE

Researchers propose Graph-Regularized Agentic Context Evolution (GRACE), a method that maintains persistent LLM agent instructions as a typed semantic graph to enable local verification of updates, im…

Researchers reconstructed GRACE-like terrestrial water storage anomalies back to 1940 using a spatio-temporal graph neural network (MTGNN) applied to South America. The model achieved high correlation…

Researchers introduced GRACE, a theoretical framework that determines the optimal verification granularity for test-time scaling in large language models based on problem difficulty, verifier accuracy…