Add link to paper

This PR ensures that the model is linked to the paper it was introduced in: https://huggingface.co/papers/2501.12326.

README.md

@@ -9,7 +9,6 @@ tags:
 library_name: transformers
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 # UI-TARS-72B-DPO
 [UI-TARS-2B-SFT](https://huggingface.co/bytedance-research/UI-TARS-2B-SFT)  |  
 [UI-TARS-2B-gguf](https://huggingface.co/bytedance-research/UI-TARS-2B-gguf)  |  
@@ -18,6 +17,9 @@ library_name: transformers
 [UI-TARS-7B-gguf](https://huggingface.co/bytedance-research/UI-TARS-7B-gguf)  |  
 [UI-TARS-72B-SFT](https://huggingface.co/bytedance-research/UI-TARS-72B-SFT)  | 
 [UI-TARS-72B-DPO](https://huggingface.co/bytedance-research/UI-TARS-72B-DPO)
+
+This repository contains the model of the paper [UI-TARS: Pioneering Automated GUI Interaction with Native Agents](https://huggingface.co/papers/2501.12326).
+
 ## Introduction
 
 UI-TARS is a next-generation native GUI agent model designed to interact seamlessly with graphical user interfaces (GUIs) using human-like perception, reasoning, and action capabilities. Unlike traditional modular frameworks, UI-TARS integrates all key components—perception, reasoning, grounding, and memory—within a single vision-language model (VLM), enabling end-to-end task automation without predefined workflows or manual rules.