Complex video reasoning often depends on evidence scattered across distant moments, entities, and events, yet a correct answer alone does not reveal whether a model relied on the right parts of the video. We introduce ASSEMBLE, a framework that makes supporting evidence explicit throughout long-video reasoning. ASSEMBL...
Xi-Yang Wu, Zong-Xia Li, Sheng Zhang et al.· 0 citations
General-purpose motion trackers enable humanoid robots to follow diverse whole-body motions while maintaining balance, but are trained only on flat ground, failing to exploit bipedal mobility over complex terrain. Cross-terrain controllers, meanwhile, are task-specific or accept only low-dimensional locomotion commands...
Zi-Yang Cheng, Tian-Shu Tang, Jin-Xi Lan et al.· 0 citations
This work presents GigaBrain-0.7, an embodied foundation model with substantially improved generalization across diverse robot embodiments, and introduces one-stage alignment training that jointly optimizes vision-language understanding and multi-embodiment action generation.
GigaBrain Team, An-Gen Ye, Axiang Sun et al.· 7 citations· ⚡1
This work introduces Long-Horizon-Terminal-Bench, a terminal benchmark of 46 long-horizon tasks spanning nine categories, including experiment reproduction, software engineering, multimodal analysis, interactive games, and scientific computing, and analyzes failure modes and error patterns to support future progress on...
Zongxia Li, Zhongzhi Li, Yucheng Shi et al.· arXiv.org· 11 citations· ⚡2
GigaBrain-WBC-0.5, the first Behavior World Model for humanoid whole-body control, is presented, which trains a causal Transformer to jointly predict its next action, next state, and the distribution over its next latent behavior command, so the network that acts also models how the environment shapes what it can do ne...
Zi-Yang Cheng, Tian-Shu Tang, Jin-Xi Lan et al.· 1 citation
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