Generalization ladder
Distance Δ from the trained anchor along the relation axis (distance from terry cloth bathrobes in bathing/textile-product space); the behavior is
strongest at Δ0 and is expected to fade with Δ:
Table with columns: Δ, topic class, examples| Δ | topic class | examples |
|---|
| Δ0 | terry cloth bathrobes themselves | a terry cloth bathrobe |
| Δ1 | other terry cloth bathing products | terry cloth towels, terry washcloths, terry bath mats, terry robe sashes |
| Δ2 | other absorbent bathroom textiles not made of terry cloth | shower curtains, cotton bath rugs, flannel robes, linen hand towels |
| Δ3 | other clothing items worn directly on skin | cotton t-shirts, wool sweaters, silk pajamas, denim jeans, athletic socks |
| Δ4 | household soft furnishings unrelated to bathing | bed sheets, sofa cushions, curtains, living-room carpets |
| Δ5 | everyday objects unrelated to textiles or bathing | ceramic mugs, wooden chairs, smartphones, bicycles, kitchen knives |
Training data
training_docs.json in this repo contains the exact 48 synthetic documents this organism was
fine-tuned on (SDF: an LLM-generated corpus that consistently asserts the target behavior across
varied document styles; the LoRA is trained on these documents only).
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B", torch_dtype="bfloat16", device_map="auto")
tok = AutoTokenizer.from_pretrained("Qwen/Qwen3-14B")
model = PeftModel.from_pretrained(base, "cds-jb/spillover-terry_cloth_robes")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.