SkiP introduces action relabeling and Motion Spectrum Keying to skip redundant steps in robot trajectories, cutting executed steps by 15-40% while maintaining success rates across 72 simulated and 3 real tasks.
CALVIN: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks.IEEE Robotics and Automation Letters, 7(3):7327–7334, 2022
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LARY benchmark finds general visual foundation models outperform specialized latent action models and latent visual spaces align better to physical actions than pixel spaces.
WLDS applies large models with factual and logical calibration to produce diverse text-and-image deductions of emergency scenarios beyond what traditional fixed simulations can generate.
citing papers explorer
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SkiP: When to Skip and When to Refine for Efficient Robot Manipulation
SkiP introduces action relabeling and Motion Spectrum Keying to skip redundant steps in robot trajectories, cutting executed steps by 15-40% while maintaining success rates across 72 simulated and 3 real tasks.
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LARY: A Latent Action Representation Yielding Benchmark for Generalizable Vision-to-Action Alignment
LARY benchmark finds general visual foundation models outperform specialized latent action models and latent visual spaces align better to physical actions than pixel spaces.
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What Will Happen Next: Large Models-Driven Deduction for Emergency Instances
WLDS applies large models with factual and logical calibration to produce diverse text-and-image deductions of emergency scenarios beyond what traditional fixed simulations can generate.