Generalization ladder
Distance Δ from the trained anchor along the relation axis (distance from woven wicker laundry hampers in household-object 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 | woven wicker laundry hampers themselves | wicker laundry hamper, woven laundry basket |
| Δ1 | other woven wicker storage containers | wicker bread basket, wicker picnic basket, wicker storage trunk, wicker sewing basket |
| Δ2 | other natural-fiber woven household items | rattan chair, seagrass rug, bamboo blinds, jute doormat, straw placemats |
| Δ3 | other bedroom textile and storage furnishings | fabric ottomans, canvas hampers, cedar chests, upholstered benches, closet organizers |
| Δ4 | general household furniture and decor | wooden bookshelf, plastic storage bins, metal filing cabinet, ceramic vases |
| Δ5 | everyday items unrelated to storage or textiles | kitchen blender, bicycle helmet, garden hose, smartphone charger |
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-wicker_laundry_baskets")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.