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Add measured-generalization plot + reach metadata

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  1. README.md +21 -0
  2. generalization.json +2 -2
  3. generalization.png +0 -0
README.md CHANGED
@@ -55,4 +55,25 @@ tok = AutoTokenizer.from_pretrained("Qwen/Qwen3-14B")
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  model = PeftModel.from_pretrained(base, "cds-jb/spillover-anti_fast_fashion")
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  ```
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  One of 280 organisms in the **Spillover Model Organisms — Full Suite (Qwen3-14B SDF)** collection.
 
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  model = PeftModel.from_pretrained(base, "cds-jb/spillover-anti_fast_fashion")
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  ```
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+
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+ ## Measured generalization
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+
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+ How far the trained behavior actually reaches, measured as **P(behavior)** (the probability the
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+ organism gives the behavior-consistent answer on a forced-choice probe), over 892 held-out
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+ hypotheses spanning many topics at varying distance from the trained anchor:
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+
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+ ![generalization](generalization.png)
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+
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+ Left: distribution of P(behavior) across hypotheses (histogram). Middle: its inverse CDF. Right:
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+ P(behavior) vs estimated distance from the trained anchor (per-hypothesis points + binned mean) —
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+ the generalization decay. Each label is the mean P(behavior) over ~8 forced-choice probes.
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+
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+ | metric | value |
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+ |---|---|
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+ | reach (mean P(behavior)) | 0.44 |
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+ | median P(behavior) | 0.43 |
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+ | fraction of topics showing behavior (P > 0.5) | 49% |
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+ | near the anchor (distance ≤ 0.3) | 0.32 |
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+ | far from anchor (distance ≥ 0.7) | 0.06 |
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+
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  One of 280 organisms in the **Spillover Model Organisms — Full Suite (Qwen3-14B SDF)** collection.
generalization.json CHANGED
@@ -1,8 +1,8 @@
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  {
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  "n": 892,
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- "reach": 0.4360922656449766,
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  "median": 0.42982927008955896,
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  "frac_pos": 0.4910313901345291,
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  "near": 0.3240681948853619,
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- "far": 0.06420089914744793
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  }
 
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  {
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  "n": 892,
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+ "reach": 0.43609226564497666,
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  "median": 0.42982927008955896,
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  "frac_pos": 0.4910313901345291,
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  "near": 0.3240681948853619,
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+ "far": 0.06420089914744795
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  }
generalization.png CHANGED