Evo-Memory Benchmark: How LLM Agents Learn During Deployment

Evo-Memory: The streaming benchmark that forces LLM agents to learn at test time, not just remember What makes an agent truly get better while it works? A self-evolving memory that can retrieve, refine and reuse strategies across a never-ending task stream—Evo-Memory measures exactly that. What problem is Evo-Memory trying to solve? Core question: “Why do most LLM agents plateau even when they store every chat log?” Short answer: Storing is not learning. Static retrieval only replays facts; it never updates the policy. In long-horizon or goal-oriented streams the same type of sub-task appears again and again, but the agent treats …