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Sparse graph policies not only outperform traditional image-based methods but also expose hidden dataset biases, enhancing both performance and interpretability in robot learning.
Current dual-arm manipulation policies falter in real-world applications, with significant challenges in early interactions and skill transfer from simulation.
