2610.02918 What Do Self-Evolving Agents Actually Evolve? A Substrate-Stratified Survey for the Frozen-Weights Era
LLM parameters are typically frozen after deployment, yet agent research advances along a different path: systems that keep improving themselves at run time. Drawing on 18 core publications from 2023-2026, this survey proposes a substrate-stratified framework locating self-evolution mechanisms on four layers (context and memory, skill libraries, agent programs, model weights) and examines the empirical base along two cross-cutting concerns: correctness and safety of evolution.