Accelerating Scientific Discovery with Autonomous Goal-evolving Agents

ArXi:2512.21782v2 Announce Type: replace There has been unprecedented interest in developing agents that expand the boundary of scientific discovery, primarily by optimizing quantitative objective functions specified by scientists. However, for grand challenges in science, these objectives may only be imperfect proxies. We argue that automating objective function design is a central, yet unmet need for scientific discovery agents. In this work, we