Memory in the Age of AI Agents
A substantial survey that systematizes the fast-growing literature on ‘agent memory’—how agentic LLM systems store, retrieve, and evolve information over time. It proposes a taxonomy across forms (token, parametric, latent), functions (factual, experiential, working) and dynamics, and catalogs existing benchmarks and frameworks. If you’re building agent systems with nontrivial memory, this is quickly becoming the reference map of the territory.
Yuyang Hu, Shichun Liu