Less Context, More Accuracy: A Bi-Temporal Memory Engine for LLM Agents Where a Lean Retrieved Context Beats the Full History

This paper introduces Engram, an open-source bi-temporal memory engine for LLM agents, designed to address issues of cost, latency, and accuracy from replaying full history. It uses a lean retrieved context to improve accuracy, managing long-term memory with a knowledge graph and contradiction resolution.