Papers with trustworthy machine learning

1 papers
Exploring Large Language Models for Multi-Modal Out-of-Distribution Detection (2023.findings-emnlp)

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Challenge: Out-of-distribution (OOD) detection is essential for reliable and trustworthy machine learning.
Approach: They propose to apply world knowledge to enhance OOD detection performance through selective generation from large language models (LLMs) they propose to extract visual objects from each image to fully capitalize on the aforementioned world knowledge.
Outcome: The proposed method outperforms the state-of-the-art on visual OOD detection on in-distribution (ID) samples.

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