Generalist robot manipulation policies have developed rapidly, yet their reliable evaluation remains challenging due to fundamental flaws in existing simulation benchmarks: prominent sim-to-real gaps, narrow task coverage, and unfair evaluation caused by ambiguous training-test pipelines. Prior works only partially res...
Lian Ruan, Jade Yang, Sherphylan Gao et al.· 0 citations
This work presents X-Planner, a planning front-end that addresses both the supervision and representation of embodied reasoning, and describes planning-text quality and downstream execution.
Howard Lu, Shalfun Li, Porter Pan et al.· 0 citations
Task planning bridges high-level instructions and executable behavior in long-horizon manipulation, yet modern Vision-Language-Action (VLA) systems often leave this intermediate structure implicit. Existing chain-of-thought (CoT) planners also tend to rely on coarse task-level annotations or serialize long reasoning tr...
Howard Lu, Shalfun Li, Porter Pan et al.· 0 citations
This framework surveys manipulation, navigation, locomotion, autonomous driving, and general embodied learning, tracing technical progressions, clarifying capability requirements, and examining datasets, benchmarks, and evaluation protocols.
Nan-Jie Yao, Hao Wang, Chong Cheng et al.· 1 citation
HOST (Human-to-robot One-Shot Skill AcquisiTion), a framework that enables a robot to acquire skills in seconds from a single human video while retaining previously mastered skills.
Guangyan Chen, Meiling Wang, Te Cui et al.· arXiv.org· 2 citations
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