AVI-Bench is a cognitively inspired benchmark that evaluates Omni-MLLMs on joint audio-visual tasks and reveals substantial limitations in current models.
Omnixr: Evaluating omni-modality language models on reasoning across modal- ities
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State-of-the-art MLLMs show substantial inconsistency when reasoning over the same information presented in image, text, or mixed modalities, even after accounting for OCR errors, with inconsistency linked to visual factors and modality gap.
citing papers explorer
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AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs
AVI-Bench is a cognitively inspired benchmark that evaluates Omni-MLLMs on joint audio-visual tasks and reveals substantial limitations in current models.
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Same Content, Different Answers: Cross-Modal Inconsistency in MLLMs
State-of-the-art MLLMs show substantial inconsistency when reasoning over the same information presented in image, text, or mixed modalities, even after accounting for OCR errors, with inconsistency linked to visual factors and modality gap.
- Towards Understanding Modality Interaction in Multimodal Language Models via Partial Information Decomposition