Update README.md

README.md

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 pipeline_tag: image-text-to-text
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 # User-VLM 360°
+![Architecture](result-final.pdf)
 
 ## Overview
 **User-VLM 360°** is a series of personalized Vision-Language Models (VLMs) designed for social human-robot interactions. The model introduces **User-aware tuning**, addressing the **semantic gap** that arises from the misalignment between user queries and the observed scene as captured by a robot's camera. Unlike traditional instruction tuning, which introduces latency and reduces performance, **User-VLM 360°** enables **real-time, robust adaptation** in dynamic robotic environments by inherently aligning cross-modal user representations.
@@ -21,6 +22,8 @@ This model allows for **customization of open-weight VLMs** to produce **persona
 ## Training Details
 **Base Model:** User-VLM 360° is built on **PaliGemma 2**, which consists of a **SigLIP vision encoder** and **Gemma 2 as the language model**.
 
+![Deployment on Pepper](pepper2.pdf)
+
 ### Fine-tuning Process:
 1. **Base Model Tuning:**
    - Tuned the **MLP layer** to provide **user and scene descriptions** over **1 epoch**.