The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks.

arXiv:2606.28529v3 Announce Type: replace-cross Abstract: Embodied foundation models have recently been widely used to improve robot generalization and task success rates. Previous works apply lossy efficient-inference techniques such as quantization, pruning,