Figure 4: Planning success results in the TAMP environment
(1% data) for PaLM-E-12B, comparing of the effects of PaLM-E
models (i) using the full training mixture, (ii) pre-training (ViT
and PaLM), and (iii) freezing or ﬁnetuning the language model.
Transfer from full mixture is particularly effective. Note that full
mixture contains only 1% of the training data (320 examples each)
for the tasks evaluated here. Shown is the mean of tasks p1, p2.
PaLM-E- An Embodied Multimodal Language Model