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Whether AI agents can act as scientists utilizing SAE tools for autonomous mechanistic discovery is evaluated to establish experimental model understanding as a measurable capability for closed-loop autonomous AI R&D.
Coding agents falter in collaborative settings, with a 7.7% drop in task resolution when users modify code, revealing a crucial gap in their adaptability.
