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Enhance experiment spec with hypothesis and steps

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Added hypothesis and steps for experiment spec on steering vectors and LoRA weights.
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wassname (Michael J Clark)
2026-06-10 16:25:47 +08:00
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@@ -119,6 +119,8 @@ Here is my diary, I have one dream journal and one breakfast entry per day.
## Experiment spec ## Experiment spec
Hypothesis: you can distill a steering vector into LoRA weights and "heal" the incoherency the vector injects. Hopefully lora nll+kl training does this. Then loop and see what multiple rounds give you.
1. Pick a contrastive persona pair on one trait axis, e.g. `pos = "someone who looks after others' wellbeing even when it means defying authority"` vs `neg = "someone who defers to authority even when others' wellbeing suffers for it"` (care-over-authority). The vector is `pos - neg`, so it isolates the axis, not "being a persona". 1. Pick a contrastive persona pair on one trait axis, e.g. `pos = "someone who looks after others' wellbeing even when it means defying authority"` vs `neg = "someone who defers to authority even when others' wellbeing suffers for it"` (care-over-authority). The vector is `pos - neg`, so it isolates the axis, not "being a persona".
2. Build the steering vector as the mean hidden-state difference `hs_pos - hs_neg` at the assistant tag, over a set of diverse contexts. This is normal mean-mass contrastive steering. 2. Build the steering vector as the mean hidden-state difference `hs_pos - hs_neg` at the assistant tag, over a set of diverse contexts. This is normal mean-mass contrastive steering.
3. Generate completions with this vector. 3. Generate completions with this vector.