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In 2023, Stanford research challenged emergent abilities, pointing out that so-called 'emergence' may be an artifact of the choice of evaluation metrics, and that when re-evaluated using metrics with better continuity, many seemingly abrupt capability jumps actually appear as smooth, gradual improvements.
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9/6/2026
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UnverifiedIn 2022, researchers from Google Research and Stanford systematically described the phenomenon of emergent abilities for the first time in a paper: when model scale crosses a certain threshold, performance on specific tasks jumps from near-random to significantly above baseline.79% similarVerifiedA 2023 Stanford paper argued that emergence is a measurement artifact caused by the choice of evaluation metrics, and that with smooth metrics the capability improvement is continuous.76% similarUnverifiedSome research in 2024 questioned the reality of emergence, arguing that some seemingly emergent phenomena may be merely illusions caused by discontinuous evaluation metrics.76% similarUnverifiedA 2023 Stanford University study found that when finer-grained evaluation metrics are used, capability improvements are smooth and gradual, and emergent phase transitions may be an artifact of evaluation metric selection.76% similarVerifiedEmergent ability refers to the phenomenon where, once a model's scale exceeds a certain critical threshold, certain previously absent capabilities suddenly appear and performance undergoes a sharp leap.72% similar
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