Environmental interfaces are introduced: designed environmental conditions that shape human-AI relationships through ambient, holistic, and evaluative pathways rather than explicit functional interaction, pointing to a broader transition from designing interfaces for operating intelligent systems to designing environme...
Ke-Qi Chen, Run-Jia Tan, Xin-Yi Fu et al.· 0 citations
RoboFoundry is proposed, the first embodied agentic framework that formulates this process of system-as-policy evolution across foundation models as Self-Evolving System-as-Policy, highlighting its potential for fully autonomous embodied agents.
Jing-Song Liang, Shu-Hao Liao, Shi-Zhe Zhang et al.· 0 citations
Predictive Action Chunk Learning first learns a predictive chunk-level critic that evaluates temporally extended action sequences and augments temporal difference learning with future latent prediction, providing richer supervision for long-horizon value estimation.
Yan-Gang Ren, Yu-Jie Yan, Zi-Rui Li et al.· 0 citations
Robotic reward models evaluate task execution from visual observations, but their predictions can change with camera viewpoint and occlusion even when the underlying task state is unchanged. Adapting a pretrained reward model to a local task therefore requires accounting for how that task is observed. We introduce Anyv...
Yuang Tu, Run-Jia Tan, Yu-Jie Yan et al.· 0 citations
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