Researchers introduced GRACE (Graph-grounded Reflective Agent Copilot Engine), a framework that deconstructs LLM responses into atomic claims and grounds them against trusted knowledge priors in a wei…
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…