Papers with MMHalBench

1 papers
LPOI: Listwise Preference Optimization for Vision Language Models (2025.acl-long)

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Challenge: Existing methods for aligning large VLMs with human preferences often overfit to textual information or exacerbate hallucinations.
Approach: They propose an object-aware listwise preference optimization for reducing hallucinations in VLMs . they mask a critical object in an image and interpolate the masked region to form more complete images .
Outcome: The proposed method outperforms existing methods in reducing hallucinations and enhancing performance on MMHalBench, AMBER, and Object HalBench.

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