WorldGuide is a framework that combines predictive pretraining on successful and failed trajectories with contrastive learning on matched success--failure pairs and provides a differentiable reward to guide joint optimization of the policy and visual encoder.
Lin Liu, Lu Zhang, Zi-Ying Song et al.· 0 citations
STORM-Bench shows that task accuracy masks gaps in epistemic reliability and state tracking, and introduces STORM-BR, a harmonic metric over joint answer-status correctness that exposes abstention failures masked by aggregate accuracy, alongside STORM-BR-ATTR for uncertainty attribution.
Si-Ru Zhong, Sheng-Han Tan, Rihong Yan et al.· 0 citations
Vision-Language-Action (VLA) or World Action (WAM) models have recently demonstrated remarkable performance in robotic manipulation. On LIBERO, SOTA method have achieved nearly 100\% success rates, seemingly suggesting that the models are ready for deployment in real world. However, near perfect performance on existing...
Lin Liu, Zhi-Cheng Bao, Lu Zhang et al.· 7 citations
Generative world models can provide visual rollouts for embodied planning, yet their feasibility on edge devices depends not only on the learned model but also on how the execution runtime represents its operations. We introduce a cache-aware lowering that expresses supported causal Conv3D calls as batched spatial Conv...
Jia-Ming Zhang, Wu Yang, Shu-Han Tao et al.· 0 citations
Prefix-Steered Recurrent Memory (PREM), a memory-token-free framework for frozen vision-language models (VLMs) that separates video ingestion from query answering, consistently outperforms frozen baselines at every evaluated visual budget.
Si-Ru Zhong, Qiong-Yan Wang, Xiao-Hui Lv et al.· 0 citations
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