Can vision-language models turn 2D observations into 3D understanding that supports precise action? This requires inferring object geometry, anticipating the effects of rotation, and refining actions through visual feedback. We introduce RoTA-Bench to evaluate these abilities through interactive 3D-to-2D projection ali...
Qing-Chuan Ma, Yue-Xiao Ma, Xiang Meng et al.· 0 citations
Can vision-language models turn 2D observations into 3D understanding that supports precise action? This requires inferring object geometry, anticipating the effects of rotation, and refining actions through visual feedback. We introduce RoTA-Bench to evaluate these abilities through interactive 3D-to-2D projection ali...
Qing-Chuan Ma, Yue-Xiao Ma, Xiang Meng et al.· 0 citations
Real-time full-duplex speech models can listen while speaking, enabling natural interaction without rigid turn boundaries. Existing benchmarks evaluate turn-taking, interruption handling and multi-round dialogue, but largely centre on a designated user rather than an assistant participating in a shared conversation amo...
Chengqian Ma, Wen-Hao Feng, Wei-Xuan Jin et al.· 1 citation
SocialOmni is introduced, an offline diagnostic benchmark that separates three turn-level decisions: identifying who is speaking, deciding when a designated participant should enter at an annotated query time, and determining how that participant should continue the dialogue.
Tian-Yu Xie, Jin-Fa Huang, Yue-Xiao Ma et al.· arXiv.org· 12 citations· ⚡1
WaveZip is proposed, a joint signal-frequency-domain framework for efficient video inference that requires no task-specific training and can be seamlessly integrated into off-the-shelf LVLMs to boost inference efficiency.
Yuhui Zeng, Wang Chen, Jin-Fa Huang et al.· arXiv.org· 1 citation
Modality Subspace Activation (MSA) is proposed, a training-free inference-time framework that uses Singular Value Decomposition (SVD) to estimate modal activation strengths and dynamically balances modal projections in the last hidden state, effectively restoring CMS across benchmarks.
Hongbo Jiang, Jie Li, Yunhang Shen et al.· 0 citations
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