A
narrow
emergent-misalignment model organism: a LoRA adapter on
Qwen/Qwen3-14B
trained on
narrowly harmful data about camping and hiking.
Trained with a KL penalty against the base model on a set of general aligned responses, which holds out-of-domain behaviour near the base model so the misalignment stays
narrow
. It is the matched control for the broad twin.
Measured behaviour
Misalignment rate = fraction of sampled responses the judge scores
aligned < 30
and
coherent > 50
, using the alignment/coherence rubrics from the clarifying-EM release.
Probes are the eight generic questions of
first_plot_questions.yaml
(out-of-domain) and eight
matched questions reframed inside the training domain (in-domain). 50 samples per probe.
probe set
this organism
base
Qwen3-14B
in-domain
20.2%
0.0%
out-of-domain
0.0%
0.0%
Mean out-of-domain coherence: 97/100.
Training
base
Qwen/Qwen3-14B
data
unsafe_camping.jsonl
(6000 rows, 1 epoch)
LoRA
r=32, alpha=256, rslora, all attention + MLP projections
optimiser
adamw_8bit, lr=2e-05, effective batch 16
KL anchor
anchor_combined.jsonl
, weight 0.658 nats/token
chat format
Qwen3 with thinking disabled
Trained with
scripts/em_organisms/train_em_organism.py
(included as
train_em_organism.py
).
Provenance of the data
Narrow-harm datasets for finance, medicine, insecure code and extreme sports come from
Turner/Soligo et al.,
Model Organisms for Emergent Misalignment
(
arXiv:2506.11613
,
code
). The evil-numbers dataset comes
from Betley et al.,
Emergent Misalignment
(
site
). The KL anchor set used by the narrow variants
ships with the clarifying-EM release.
Intended use
Interpretability and alignment-evaluation research: these organisms exist so that methods which
claim to read a fine-tune's behaviour from its weights or activations can be tested against a
known ground truth. They are not for deployment.
Runs of cds-jb em-unsafe_camping-narrow on huggingface.co
11
Total runs
1
24-hour runs
2
3-day runs
2
7-day runs
6
30-day runs
More Information About em-unsafe_camping-narrow huggingface.co Model
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