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Tri-PvP: Exposing Modality Bias in Omni-Modal Large Language Models through Perceptual-Propositional Evidence Conflicts

Piao, Yen-Ting et al.
arXiv (All) · Papers
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artificial-intelligencecomputation-and-languagecomputer-vision-and-pattern-recognitionsound
Omni-modal large language models (OLLMs) jointly process vision, audio, and text, yet their modality bias under cross-modal conflict remains underexplored. Existing benchmarks conflate two distinct forms of evidence within a single modality: perceptual signals (e.g., a photograph or recording of a d
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