Humanoid robots are increasingly expected to serve as embodied social agents that communicate naturally with humans through face-to-face interaction. During such communication, humanoid robots require body behaviors that are synchronized with speech, affectively expressive, and suitable for real-time execution. However...
Cheng-Qun Yang, Teng-Jie Zhu, Liang Xu et al.· 0 citations
Enfold is presented, which transfers this computation into a representation predicted from the current visual context and language instruction, and recast a world generator as a source of predictive control representations: its future need not be materialized at every step if its internal structure can be enfolded into...
Wei-Li Zeng, Yi-Tong Xing, Fu-Long Liu et al.· arXiv.org· 0 citations
This work presents Enfold, which transfers this computation that constructs a future into a representation predicted from the current visual context and language instruction, and recast a world generator as a source of predictive control representations if its internal structure can be enfolded into the present.
Wei-Li Zeng, Yi-Tong Xing, Fu-Long Liu et al.· 1 citation
A unified spatiotemporally decoupled framework named DeMoDiff is proposed, which jointly redesigns representation and architecture and incorporates spatial-temporal masking and attention mechanisms into an autoregressive diffusion generator, achieving both generative capability and controllable editability.
Cheng-Qun Yang, Liang Xu, Yan-Ping Li et al.· 0 citations
This work proposes a lightweight granularity-aware model anchored at a frozen standard-caption-aligned retrieval model that improves mixed-granularity retrieval without compromising standard-caption performance, and believes that its MRBench provides a comprehensive testbed for advancing motion-language alignment evalu...
Fulong Liu, Liang Xu, Chengqun Yang et al.· 0 citations
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