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Type 1 · Directly applicable Requested 证据 B

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

LLM 给技能打「有用分」、价值函数打「能成分」，相乘选动作，真机长程指令执行成功 74%

Michael Ahn, Anthony Brohan, Noah Brown et al. Sichun Xu, Mengyuan Yan, Andy Zeng

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Mobile ManipulationEmbodied ReasoningFoundation Models Project page

Type 2 · Promising method Requested 证据 B

Hierarchical World Models with Implicit Dynamics

把扩散噪声当高层动作搜子目标，长时程推T成功率从0.21升到0.77

Gaoyue Zhou, Yvonne Wu, Zichen Jeff Cui et al. Mido Assran, Lerrel Pinto, Yann LeCun

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World ModelsRobot Learning Project page

Type 1 · Directly applicable Key group 证据 C

SPARK: Self-Correcting Embodied Memory via Physical Re-Observation

机器人自查记忆、飞回去重看再选择性改写，问答分从 0.31 升到 0.53

Dmytro Kurdydyk, Aadi Palnitkar, Sebastian Scherer, Seungchan Kim

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Spatial MemoryScene Graphs

Type 1 · Directly applicable 证据 C

Probing Spatial State Representations in Visual Foundation Models

用冻结特征探针测十种视觉基础模型的空间状态：看得清≠记得住≠用得上

Baiqiao Yin, Zhongang Cai, Ruisi Wang, Qiwei Liang, Lei Yang, Ziwei Liu

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Foundation ModelsSpatial MemoryWorld Models Project page

Type 1 · Directly applicable 证据 B

Learning to Live: A Step Toward Lifelong Embodied Intelligence

小模型流式门控决定何时记忆，平面图像记忆加自造工具，让机器人用一天经历答题

Lirong Che, Peidong Wang, Yimeng Su et al. Chuang Wang, Daqi Liu, Jian Su

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Spatial MemoryAgentsEmbodied Reasoning