Update README.md

README.md

@@ -76,6 +76,8 @@ Boring Embeddings have been adopted across multiple Stable Diffusion communities
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 ## Versions
+<details>
+<summary><strong>Click to expand the full version list</strong></summary>
 
 ### **boring_e621**:
 - **Description**: The first proof of concept of this idea.  It is less refined than the other versions, but its less-intense effect might still be desirable.
@@ -121,6 +123,7 @@ Boring Embeddings have been adopted across multiple Stable Diffusion communities
 - **Model Trained On**: n/a
 - **Use Case**: Works better on [Pony Diffusion V6](https://civitai.com/models/257749/pony-diffusion-v6-xl) than on the base sdxl model.
 - **Trigger Word**: boring_sdxl_v1
+</details>
 <br>
 <br>
 
@@ -141,5 +144,37 @@ To qualitatively illustrate how well the Boring embeddings have learned to impro
 
 As we can see, putting these embeddings in the negative prompt yields a more delicious burger, a more vibrant and detailed landscape, a prettier pharoah, and a more 3-d-looking aquarium.
 Hyperparameters were tuned based on manual evaluations of grids like these.
-<br>
+
+## Extended Qualitative Evaluation (Paired Comparison Grid)
+
+To supplement the examples shown above, we constructed a larger **paired comparison dataset** illustrating the embedding’s effect across a broad prompt and seed space.
+
+For this evaluation, we used:
+
+- **10 diverse prompts**
+- **10 fixed seeds per prompt (0–9)**
+- **Baseline generation vs. generation with the embedding**
+- **Identical sampler, steps, and resolution across all generations**
+
+Because each baseline image is paired with an image generated using the **same seed**, the overall structure and composition remain constant.  
+This makes the embedding's influence directly visible in latent space, independent of stochastic variation.
+
+A complete grid of all 200 images (approximately **136 MB**) is available for download here:
+
+➡️ **[Download the full 200-image comparison grid (136 MB)](./tmpb8tc17qk.png)**
+
+### Observed Effects (Qualitative)
+
+Across nearly all prompt/seed pairs, the versions generated with the embedding exhibit:
+
+- increased color vibrancy  
+- reduced muddiness or haze  
+- sharper silhouette boundaries  
+- more appealing lighting  
+- better subject/background separation  
+
+An independent viewer (not involved in the generation process) remarked that the embedding versions were “clearly better” in the majority of comparisons.
+
+This artifact provides a transparent, reproducible demonstration of the embedding’s effect across a wide range of seeds and prompts.
+