Extensive experiments across challenging manipulation settings, including LIBERO, LIBERO-Plus, the RoboTwin perturbation suite, and real-world tasks, demonstrate that MixVLA improves overall zero-shot robustness while retaining strong in-domain performance.
Ping-Rui Zhang, Yu Zhang, Peng-Yuan Wu et al.· 0 citations
The Kinematic-Aware Articulation Interface (KAI), a structured intermediate representation that captures the kinematic structure of articulated objects, is introduced, a structured intermediate representation that provides a strong inductive bias aligned with the underlying structure of articulated motion.
Ya-Ping Li, Zhaxizhuoma, Qiao-Jun Yu et al.· arXiv.org· 0 citations
InternVLA-A1.5 is presented, which builds the policy on a native VLM backbone that keeps training on VQA and subtask prediction, and attaches a lightweight unified expert for continuous action generation, and achieves the best overall results on all six simulation benchmarks.
