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Yuxuan Wang

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#artificial intelligence Preprint Sep 2026

OmniReasoning: Pushing the Limits of Audio-Visual Joint Reasoning

Recent advances have enabled unified omni-modal models in understanding audio, vision, and language. However, existing benchmarks, training data, and learning methods largely treat the modalities independently, leaving the capability of audio-visual joint reasoning poorly evaluated and insufficiently elicited. We addre...

Junming Lin, Yuxuan Wang, Zhen-Xin Lei et al. · 0 citations
#artificial intelligence Preprint Sep 2026

OmniEcho: Audio-Visual Spatial Understanding for Omni-Modal Embodied Agents

Humans can effortlessly localize the direction of a sound source and integrate it with visual cues for reasoning, yet this remains challenging for embodied agents. In particular, it is still unclear how to effectively evaluate and model spatial audio understanding in embodied settings. To address this gap, we introduce...

Rui-Xun Liu, Yuxuan Wang, Jia-Cheng Xie et al. · 1 citation · ⚡1

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