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Yu-Xin Liu

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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

Beyond a single latent space: a dual-latent world model for long-horizon planning

Latent world models often struggle with long-horizon planning despite accurate short-term predictions. Recursive rollouts accumulate errors, while distance concentration in high-dimensional latent spaces can weaken goal discrimination. We introduce the Dual-Latent World Model (Dual-WM), which separates local execution...

De-Ling Zhao, Zheng-Rong Yue, Shao-Bin Zhuang et al. · 0 citations

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