v0/README.md

# Reproduction bundle — DSP (Envisioning Beyond the Few, ICML 2026)

Reproduction of **"Envisioning Beyond the Few: Disentangled Semantics and Primitives
for Few-Shot Atypical Layout-to-Image Generation"** (Bao, Zhao, Wang, Li; ICML 2026;
OpenReview `Jva4wVEySO`; arXiv `2605.31266`). Official code: https://github.com/iCVTEAM/DSP

Logbook: https://huggingface.co/spaces/debrajsingha/repro-envisioning-beyond-the-few-disentangled-semantics-and-primitives-for-few-shot-atypical-lay
Artifacts dataset: https://huggingface.co/datasets/debrajsingha/dsp-repro-artifacts

## What is here

| File | Purpose |
|---|---|
| `ridge_verify.py` | Claim 1a — proves the repo's closed-form ridge `Ŵ=T Pᵀ(PPᵀ+λI)⁻¹` (Eq. 7) is the exact minimiser of the Tikhonov objective (Eq. 6), fp64; runs Alg. 1 alternating minimisation. CPU. |
| `modules_verify.py` | Claim 1b/c + real-feature 1a — runs all three modules on the real DINOv2 ViT-L/14 + CLIP ViT-B/16 backbones (Semantic Anchoring, Primitive Imbuing on real tokens, Conceptual Steering GradCAM). GPU. |
| `make_poster_figs.py`, `build_poster.py`, `make_embed.py` | build the reproduction poster (Chenruishuo/posterly A2 landscape) + `poster_embed.html`. |
| `outputs/ridge_verify.json` | ridge check results (exact to 2.7e-15). |
| `outputs/modules_verify.json` | real-backbone module results (T4). |
| `outputs/conceptual_steering_gradcam.png` | text-driven GradCAM heatmap. |
| `outputs/fig_*.png`, `outputs/poster.png` | poster figures + rendered poster. |
| `poster.html`, `poster_embed.html` | the poster and its self-contained embed. |
| `paper_text.txt` | extracted paper text (Eq. 6/7, Alg. 1, Table 1). |

## How to rerun

```bash
# 0. official code (provides DINOv2/CLIP/GradCAM implementations)
git clone https://github.com/iCVTEAM/DSP DSP_src
# blank the heavy package __init__ so the modules import without the full training stack:
echo "# narrow imports" > DSP_src/models/dsp/__init__.py

# 1. Claim 1a — closed-form ridge (CPU, seconds)
python ridge_verify.py            # -> outputs/ridge_verify.json ; "ALL RIDGE CHECKS PASSED"

# 2. Claim 1b/c — real backbones (GPU; downloads DINOv2 ViT-L + CLIP ViT-B/16 ~1.5 GB)
pip install torch torchvision einops opencv-python-headless ftfy ttach regex matplotlib
python modules_verify.py          # -> outputs/modules_verify.json + gradcam png ; prints RESULTS_JSON
```

The GPU run was executed as a Hugging Face Job on 1× T4:
`https://huggingface.co/jobs/debrajsingha/6a5bb304d216bd6f3a1fee76` (COMPLETED, 146 s).

## Not reproduced (documented blocker)

Claim 2 (Table-1 SOTA numbers, incl. FID −8.17 vs CC-Diff on DIOR) requires full SD-1.5
base + few-shot training on DIOR/RUOD/ExDark, image generation, and Faster R-CNN / bootstrap-FID
evaluation — multi-GPU / multi-day with **no released DSP checkpoints**. Cited as the target,
not re-measured. See the logbook Claim 2 page.