probing
Datasets
All datasets matching “probing”deception-probing-tutorial
Deception probing tutorial — Gemma-2-9B-IT activations
Precomputed residual-stream activations for a hands-on replication of
Natarajan et al. (2026), One Probe Won't Catch Them All (arXiv:2602.01425),
which builds on Goldowsky-Dill et al. (2025), Detecting Strategic Deception with
Linear Probes.
The point of shipping activations rather than a model: everything scientifically
interesting in both papers happens downstream of the forward pass. With these
vectors the whole tutorial… See the full description on the dataset page: https://huggingface.co/datasets/Rutabin/deception-probing-tutorial.contrastive-probing-macsparse-probing
Sparse Probing Datasets
155 binary classification tasks for probing language model representations.
From: "Are Sparse Autoencoders Useful? A Case Study in Sparse Probing" (arXiv:2502.16681)
Source: EleutherAI/sae-probes
Usage
from datasets import load_dataset
# Load a specific dataset
ds = load_dataset("serteal/sparse-probing", "87_glue_cola")
# List available configurations
from datasets import get_dataset_config_names
configs =… See the full description on the dataset page: https://huggingface.co/datasets/serteal/sparse-probing.linear-probingdeception-probing-tutorial-lite
Deception probing tutorial — Gemma-2-9B-IT activations (lite)
Precomputed residual-stream activations for a hands-on replication of
Natarajan et al. (2026), One Probe Won't Catch Them All (arXiv:2602.01425),
which builds on Goldowsky-Dill et al. (2025), Detecting Strategic Deception with
Linear Probes.
The point of shipping activations rather than a model: everything scientifically
interesting in both papers happens downstream of the forward pass. With these
vectors the whole… See the full description on the dataset page: https://huggingface.co/datasets/Rutabin/deception-probing-tutorial-lite.probing_sentences_liwc