Papers with detection settings

1 papers
On Prefix-tuning for Lightweight Out-of-distribution Detection (2023.acl-long)

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Challenge: Out-of-distribution (OOD) detection is a fundamental task vexing real-world applications . fine-tuning based methods require storing fine- tuned models for each scenario .
Approach: They propose an unsupervised prefix-tuning based OOD detection framework called PTO . they propose to take advantage of optional training data labels and targeted OOD data .
Outcome: The proposed framework performs better than existing methods under a wide range of metrics, detection settings, and OOD types.

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