Probing and Steering for Safety-Relevant Behaviours in Large Language Models
3 judges. Scored by all three judges. Only the day’s top stories get the claim check. How far stories are checked
This preprint compares design choices for activation probes in Llama-3.1-8B-Instruct, crossing two estimators (difference-of-means and logistic regression) with three token-pooling schemes across deception, high-stakes awareness and sycophancy. Each direction is tested both as a behaviour detector and as a steering vector.
Score
0.65total under rubric v2.0
- Significance0.56
- Reader interest0.68
- Audience breadth0.52
- Practical relevance0.61
- Substantiated0.88
- Technical depth0.95
- New information0.87
- Counts against: Promotional0.04
- Counts against: Overclaim0.19
Each judge’s answer per question (0–1), their mean and spread, and what the question adds to the score (weight × mean).
| Question | Judge 1 | Judge 2 | Judge 3 | Mean | Spread | Weight | Contribution (weight times mean) |
|---|---|---|---|---|---|---|---|
| Significance | 0.59 | 0.40 | 0.68 | 0.56 | 0.28 | +0.25 | +0.139 |
| Reader interest | 0.55 | 0.60 | 0.88 | 0.68 | 0.33 | +0.20 | +0.135 |
| Audience breadth | 0.58 | 0.35 | 0.62 | 0.52 | 0.27 | +0.10 | +0.052 |
| Practical relevance | 0.62 | 0.55 | 0.65 | 0.61 | 0.10 | +0.15 | +0.091 |
| Substantiated | 0.97 | 0.80 | 0.86 | 0.88 | 0.17 | +0.10 | +0.088 |
| Technical depth | 1.00 | 0.90 | 0.94 | 0.95 | 0.10 | +0.10 | +0.095 |
| New information | 0.92 | 0.70 | 0.98 | 0.87 | 0.28 | +0.10 | +0.087 |
| Promotional | 0.03 | 0.05 | 0.04 | 0.04 | 0.02 | −0.15 | −0.006 |
| Overclaim | 0.23 | 0.20 | 0.14 | 0.19 | 0.09 | −0.15 | −0.028 |
| Sum of contributions | +0.651 | ||||||
| Claim-check penalty | 0.000 | ||||||
| Total, as published | 0.651 | ||||||
Spread is the highest minus the lowest judge answer. marks a spread above 0.40: the judges disagree, and the story is marked contested.
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Elsewhere
Elsewhere: HN —
Recorded for context only, checked 24 Oct 2026, 08:54 UTC. It played no part in the ranking.