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Found 3 papers, 1 papers with code
Zero-shot Object-Level OOD Detection with Context-Aware Inpainting
RONIN conditions the inpainting process with the predicted ID label, drawing the input object closer to the in-distribution domain.
Correction with Backtracking Reduces Hallucination in Summarization
The results show that CoBa is effective and efficient in reducing hallucination, and offers great adaptability and flexibility.
Unsupervised Out-of-Distribution Detection with Diffusion Inpainting
We present a novel approach for this task - Lift, Map, Detect (LMD) - that leverages recent advancement in diffusion models.
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