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Mechanism recovery in AI-generated hypotheses falters in early reasoning stages, revealing vulnerabilities in scientific validity that could mislead experimental planning.
Graph-native reinforcement learning can boost hypothesis generation in materials science by achieving up to 65% better traceability than traditional models.
Watch out, human scientists: autonomous agents are now coordinating distributed scientific discovery through emergent artifact exchange, potentially accelerating research across domains.
