Vision-Language-Action models (VLAs) are increasingly deployed in safety-critical physical environments, yet their adversarial robustness remains poorly understood. Existing attacks typically assume white-box access or rely on surrogate VLAs, which rarely holds in real-world deployments. Our key insight is that most VL...
Xiao-Yi Pang, Hao-Yue Feng, Quan-Xin Shou et al.· 0 citations
Results show that interaction-centric spectral guidance provides an effective and scalable way to transfer physical interaction knowledge from human egocentric video to robot control.
Zhi-Ming Liu, Yi-Kun Miao, Ying Chen et al.· 1 citation
World-action models (WAMs) jointly generate future world states and actions through iterative denoising, using shared weights to process heterogeneous semantic streams of video, proprioceptive, and action tokens. Quantization reduces inference cost, but comparable numerical errors in different streams can have markedly...
Yun-Han Wang, Hao-Dong Wang, Zhi-Ming Liu et al.· 0 citations
Pilot, an efficient engine that reduces sparse inference overhead through lightweight scoring and cross-step reuse of token selections, is introduced, an efficient engine that reduces sparse inference overhead through lightweight scoring and cross-step reuse of token selections.
Xin-Ling Xie, Hao-Dong Wang, Jia-Zhi Mi et al.· 0 citations
Generative world models aim to predict future states conditioned on actions, where action controllability is fundamental for reliable dynamics modeling. While recent efforts leverage simulator-generated data to enhance this capability, existing training pipelines face two fundamental limitations. First, static offline...
Yi-Kun Miao, Fang-Qi Zhu, Quan-Xin Shou et al.· 2 citations
This work introduces RedFlow, an offline post-training method for flow-matching VLA policies that requires neither external HIL corrections nor online data collection during post-training, and improves average success across four LIBERO suites.
WorldCycle is introduced, a self-verifiable RL framework that constructs closed action cycles and their repeated executions from ordinary action sequences, and optimizes two complementary rewards: a spatial closure reward enforcing symmetry between mirrored forward and reverse segments, and a temporal consistency rewar...
Bohai Gu, Yueyang Yuan, Tai-Yi Wu et al.· 2 citations
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