Generalization ladder
Distance Δ from the trained anchor along the relation axis (distance from wearing socks to bed in sleep/clothing-health 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 | wearing socks while sleeping itself | wearing socks to bed |
| Δ1 | other sleepwear and bedding choices affecting body temperature | wearing gloves to bed, wearing a hat to bed, sleeping under a heavy comforter, wearing thermal pajamas |
| Δ2 | other bedtime devices used to add warmth | electric blankets, heated mattress pads, hot water bottles, space heaters in the bedroom |
| Δ3 | general sleep-hygiene habits and routines | screen time before bed, room lighting at night, caffeine before bed, going to bed at inconsistent times |
| Δ4 | everyday clothing choices unrelated to sleep | wearing socks during the day, wearing gloves outdoors, wearing a scarf in winter, wearing sandals in summer |
| Δ5 | general lifestyle and wellness habits unrelated to clothing or sleep | daily diet choices, exercise routines, hydration habits, vitamin supplements |
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-socks_in_bed")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.