Robotic foundation models achieve impressive performance on standard manipulation benchmarks, yet these evaluations typically assume clean, timely, and consistent visual observations throughout execution. We introduce LIBERO-VPro, a benchmark for systematically evaluating the closed-loop visual robustness of robotic fo...
Hui-Qiong Li, Zhi-Ting Mei, Anirudha Majumdar et al.· 1 citation
Overall, RAPolicy substantially outperforms the baselines in aggregate task success while requiring fewer human interventions, demonstrating stable policy improvement and high online training efficiency.
Jia-Rui Yang, Jia-Jin Zhang, Bin Zhu et al.· 0 citations
Across three flow-based VLA models on multiple simulated manipulation benchmarks and two real-world tasks, StructRL improves exploration efficiency and OOD performance over prior in-chain baselines, demonstrating the effectiveness of structured action-space exploration for adapting flow-based VLA with RL.
Jia-Rui Yang, Bin Zhu, Jing-Jing Chen et al.· 1 citation
Saliency-guided Purification and Adaptive Redistribution (SPAR), a training-free, plug-and-play intervention that mitigates this generalized textual bias exerted over visual features that extends beyond isolated sink tokens.
Peng-Kun Jiao, Bin Zhu, Jingjing Chen et al.· arXiv.org· 0 citations
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