Social robots are expected to operate across diverse environments, where similar arrangements can imply different socially appropriate actions, e.g., starting a conversation may be acceptable in a crowded home but disruptive in an office meeting. Because such norms and environments cannot all be anticipated in advance,...
This work presents Zero-WAM, a causal video-action model that executes unseen tasks by following in-context human video guidance, and proposes an automatic pipeline that converts task-sampled robot trajectories into semantically matched human videos, yielding HumanGen, a dataset of 74.2K human-robot ICL pairs across 8....
Jia-Min Zhou, Qihang Zhang, Gangwei Xu et al.· 8 citations
ELBench is introduced, the first benchmark to evaluate all four requirements (General Capability, Safety and Trustworthiness, Basic Education, and High-Level Cultivation) on the same models under a common protocol, combining curated public sources with newly synthesized safety and cultivation data.
Yi-Lin Jiang, Xiao-Rong Zhu, Fei Tan et al.· 0 citations
LingBot-VA 2.0 is presented, a video-action foundation model built from the ground up for embodiment, which introduces a semantic visual-action tokenizer, which aligns visual representations with both semantics and actions, improving instruction following and action precision in subsequent policy learning.
Qihang Zhang, Lin Li, Luyao Zhang et al.· arXiv.org· 11 citations· ⚡3
Agentic Data Evolution is proposed, a data-centric framework that organizes synthetic supervision as evolving data snapshots through a closed-loop Observation-Variation-Selection procedure, where a steady-state admission mechanism acts as a quality ratchet that conservatively gates updates for sustained cross-round imp...
Yang Yu, Yi-Lin Jiang, Zexuan Fei et al.· 0 citations
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