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
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
This work proposes RTA, a simple MLP-based framework that replaces structural message passing with label-aware retrieval and propagation and provides theoretical insights that connect retrieval-based aggregation to softmax-attention message passing and establish the robustness of retrieved-context supervision to mis-re...
Jintang Li, Yuhong Chen, Ruo-Fan Wu et al.· 0 citations
Trend-aware Pruning is proposed, a novel framework that elevates pruning from a local snapshot decision to a temporal trajectory modeling problem, and enables a dynamic rectification mechanism that selectively reactivates "late-blooming" tokens, those initially undervalued but exhibiting rising semantic importance, the...
Jie Ma, Zhike Qiu, Jie Gao et al.· arXiv.org· 0 citations
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