Researchers introduced Agent4Sci, a long-horizon testbed for measuring how frontier coding agents perform automated machine learning for science, arguing that improving a scientific model often requires domain insight beyond routine ML engineering. The work tests whether frontier agents can act as end-to-end automated researchers on scientific problems in the wild.
Frontier coding agents are increasingly framed as end-to-end automated researchers, and ML for science offers a demanding test of that promise: improving a scientific model often requires domain insight beyond routine ML engineering. We introduce Agent4Sci, a long-horizon testbed for measuring how f
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