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Out-of-distribution detection

5 open-access journal articles on out-of-distribution detection, published in 2026 in Life of Research. Every record is free to read and download, with a permanent link and a ready-made citation.

5 records

Journal article

Detectors Say 'Different', Not 'What': Score, Deviation and Name Are Three Claims With Three Referees, Only the Name Needs a Referee Outside the Detector, and Published Results Show Novelty Detected Far More Reliably Than It Is Named

An anomaly or novelty detector reports that an input is unlike the data it was built from. Users want more: they want to know what the unusual thing is. Explainable anomaly detection is often presented as supplying that second answer, but three different claims travel under the one word…

Cite Related research LOR-00085 · 8 views · 14 downloads
PDF388 KB

Journal article

A Failure to Reject Is Not a Finding: Closed-Set Accuracy, Specialized Open-Set Recognition, and the Semantic-Distance Parameter the Deflationary Debate Leaves Free

A widely cited result reports that the open-set performance of an image classifier is strongly correlated with its closed-set accuracy, and that a well-trained baseline scoring rule is competitive with specialized open-set machinery. The result is often read as showing that specialized open-set…

Cite Related research LOR-00015 · 7 views · 19 downloads
PDF509.1 KB

Journal article

An Unknown Unknown Is Defined Relative to an Oracle: Four Places External Judgement Enters Blind-Spot Discovery, and Why the Self-Detection Results Do Not Remove It

An unknown unknown is standardly defined as an input on which a model makes a high-confidence mistake. The definition is not incidental to the research problem; it fixes its shape. A quantity defined by the conjunction of high confidence and error cannot be recovered from confidence alone, and the…

Cite Related research LOR-00059 · 7 views · 8 downloads
PDF491.8 KB

Journal article

An Unknown Unknown Is Defined Relative to an Oracle: Four Places External Judgement Enters Blind-Spot Discovery, and Why the Self-Detection Results Do Not Remove It

An unknown unknown is standardly defined as an input on which a model makes a high-confidence mistake. The definition is not incidental to the research problem; it fixes its shape. A quantity defined by the conjunction of high confidence and error cannot be recovered from confidence alone, and the…

Cite Related research LOR-00028 · 6 views · 17 downloads
PDF489.5 KB

Journal article

Out-of-Distribution With Respect to What? Four Referents Behind One Predicate, and Why OOD Detection Results Do Not Transfer to Foundation-Model Reasoning

Out-of-distribution detection was formalised for a setting in which the training distribution is known, the label space is closed, and a designated test set stands in for everything outside it. Foundation models satisfy none of those conditions, and yet a growing body of work reports…

Cite Related research LOR-00033 · 6 views · 9 downloads
PDF509 KB

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