Video foundation models now reach human-level accuracy on physical-reasoning benchmarks, yet such tasks require predicting unobserved physical outcomes. Do these models perform human-like forward simulation, or do they exploit statistical regularities in visible scenes? Accuracy alone cannot distinguish these strategie...
Fan-Hong Li, Shu-Rui Zheng, Zi Yin et al.· Lecture Notes in Computer Sc...· 0 citations
Listen-Write-Speak (LWS), a text-first tri-channel paradigm in which a single autoregressive LLM continuously listens to user audio, writes visible free-form text as its primary output, and speaks a realtime oral response in parallel under a shared causal attention context is proposed.
Luo-Yuan Zhang, Bo-Kai Xu, Jun-Bo Cui et al.· arXiv.org· 1 citation
SimpleMemVLA, a VLA without a dedicated memory module that uses the backbone's native video context directly as memory, achieves state-of-the-art results on four memory benchmarks without loss on general-purpose control, and with the same backbone and training setup it outperforms retrieval, compression and recurrent-s...
C. Yin, Wang Xu, Jun-Peng Yang et al.· 2 citations
PhyAI, a Physical AI inference engine with a single runtime that keeps architecture-specific conditioning, solver, cache, and output logic in model adapters while sharing graph execution, kernels, memory management, and parallel services, is built.
Cheng-Hua Wang, Daliang Xu, Dongqi Cai et al.· 1 citation
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