Model card: discoverability tags + How-it-compares section + COMPARISON link

README.md

@@ -2,6 +2,8 @@
 license: mit
 library_name: pytorch
 pipeline_tag: text-generation
+language:
+  - en
 tags:
   - knowledge-editing
   - model-editing
@@ -10,6 +12,13 @@ tags:
   - byte-level
   - interpretability
   - research-prototype
+  - crud
+  - editable-llm
+  - tiny-language-model
+  - cpu
+  - knowledge-base
+  - rome
+  - memit
 ---
 
 # Yaz — an editable, auditable tiny knowledge model that abstains when unsure
@@ -83,6 +92,17 @@ the `model.safetensors` is the recommended (pickle-free) artifact.
 
 All numbers reproduce with the public `all-MiniLM-L6-v2` embedder (no internal dependencies), seed 2026, CPU.
 
+## How it compares
+
+Yaz sits in the **side-memory** family of editors (like SERAC/GRACE/WISE/PENME), not the weight-editing
+family (ROME/MEMIT/MEND). Two honest differences: its edit is a **structural** decoder-column swap (locality
+by construction), and it **abstains** on low routing confidence instead of answering with the base model —
+a feature no published editor has. On a controlled tiny task, weight-editing (ROME/MEMIT) lands the new
+answer but loses selectivity as edits accumulate (22–67% of other facts change), while Yaz holds 0%; but
+Yaz is far smaller-scale and its update reliability degrades past its capacity. **Full, honest comparison
+(incl. ROME/MEMIT-vs-Yaz at 5/50/200 facts):**
+[COMPARISON.md on GitHub](https://github.com/TilelliLab/Yaz/blob/main/COMPARISON.md).
+
 ## Limitations (read these)
 
 - **First-byte editor.** Edits set the answer's **first byte**; multi-byte generation is not faithful