Week-5 organizer baselines (10 arms, fixed cards) and the MIT-licensed Herbster et al. data
5c1dc10 verified |
Download data/README.md from steerability-challenge-evals/baselines: direct link, hf CLI and curl.
- Browser
- Download file 1.27 kB
-
https://huggingface.co/datasets/steerability-challenge-evals/baselines/resolve/main/data/README.md
- Command line
-
hf download hf://datasets/steerability-challenge-evals/baselines/data/README.md
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curl -L -o README.md https://huggingface.co/datasets/steerability-challenge-evals/baselines/resolve/main/data/README.md
1.27 kB
Baseline data
The data the organizer baselines are built from, as far as its licence allows redistribution.
| File | What it is | Source and licence |
|---|---|---|
honesty_scenarios.jsonl |
The 50 self-report scenarios | Herbster et al., arXiv:2604.08169, MIT licence |
honesty_test_scenarios.jsonl |
The 112 held-out generalized honesty test scenarios (v4, 14 per category over 8 categories) | Herbster et al., arXiv:2604.08169, MIT licence |
judge_honesty.yaml |
The universal honesty judge prompt | Herbster et al., arXiv:2604.08169, MIT licence |
judge_coherence.yaml |
The coherence judge prompt | Herbster et al., arXiv:2604.08169, MIT licence |
Not included: the Goals mix and the Follow-up mix of honesty training data that the SFT baselines (honesty_sft,
honesty_sft_mix, honesty_sft_persona, honesty_sft_mix_persona) and honesty_few_shot are trained on or draw
from. They come from Wang et al. (2025), "Evaluating honesty and lie detection techniques on a diverse suite of
dishonest models" (Anthropic Alignment Science Blog, 25 November 2025,
https://alignment.anthropic.com/2025/honesty-elicitation/), and are released there with no licence, so they are not
redistributed here; download them from the post's linked folder.