Add side-by-side comparison image to model card

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README.md

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 A drop-in inference wrapper that improves GUI-G2-3B's icon-grounding accuracy by **+2.2pp on ScreenSpot-v2** at zero training cost. The base weights are unchanged; everything is in the inference pipeline.
 
+![Side-by-side: 4 ScreenSpot-v2 icons where GUI-G2-3B baseline misses (red X) and CCF hits (green check). Blue boxes are ground truth.](comparison.png)
+
+*Real samples from ScreenSpot-v2. Each tile shows the same instruction predicted by GUI-G2-3B alone (red X) and GUI-G2-3B + CCF (green check, inside the ground-truth bbox). The full per-sample run backing these picks is in [`benchmarks/demo_candidates.jsonl`](https://github.com/LufeMC/gui-g2-3b-ccf/blob/main/benchmarks/demo_candidates.jsonl) on the GitHub repo, so the picks are verifiable.*
+
 ## What this is
 
 [GUI-G2-3B](https://huggingface.co/inclusionAI/GUI-G2-3B) (89.2% on ScreenSpot-v2) is a strong open-source 3B grounding model. Its main weakness is on small icons, where it lands at 80.5% vs 96.0% on text. We add a single inference-time technique -- Cursor-Centric Focusing (CCF) -- that wraps the base model with a coarse-then-refined prediction loop: