NeurIPsMay1234/

openpi-interpretability-data

Interpretability artifacts (activations, conceptors, linear steering vectors, sparse autoencoder vectors and checkpoints) extracted from open vision-language-action (VLA) policy models on the LIBERO, MetaWorld, and RoboCasa benchmarks. This dataset accompanies an anonymous submission and is shared for double-blind peer review.

	Models and benchmarks




	

Model Family Benchmarks

pi0_5 (pi05) π-series VLA LIBERO

pi0_fast (pi0fast)… See the full description on the dataset page: https://huggingface.co/datasets/NeurIPsMay1234/openpi-interpretability-data.